CN110716552A

CN110716552A - Novel driving system for automobile, train, subway and airplane

Info

Publication number: CN110716552A
Application number: CN201911091758.XA
Authority: CN
Inventors: 朱云
Original assignee: Individual
Current assignee: Individual
Priority date: 2019-11-11
Filing date: 2019-11-11
Publication date: 2020-01-21

Abstract

The invention discloses a novel driving system for automobiles, trains, subways and airplanes; driving automobiles, trains, subways, and airplanes in accordance with a robot system instead of humans; the novel driving technology of the automobile, the train, the subway and the airplane, the robot-driven automobile, the train, the subway and the airplane are researched and invented; operating car, train, subway and airplane operating floor equipment; the technology has the advantages that traffic accidents are reduced, traffic congestion is reduced, driving is guaranteed, and flying is stable in running, and the technology is convenient and quick to use, rapid to operate, more humanized, more practical and more relieved; is suitable for the future development situation.

Description

Novel driving system for automobile, train, subway and airplane

Technical Field

The invention relates to a novel driving system for automobiles, trains, subways and airplanes; is characterized in that: automobiles, trains, subways, and airplanes are driven by the robotic system instead of humans; operating car, train, subway and airplane operating table equipment.

Background

When the automobile, the train, the subway and the plane have faults in the unmanned process, the judgment experience finds out the faults, manual repair is carried out, the time is delayed, misoperation is easy, and major accidents are caused, which is described in another patent 2019103772482; automatic fault repair methods for automobiles, trains, subways, and airplanes are found; the method mainly analyzes the automatic finding and automatic repairing of the faults of the automobiles, trains, subways and airplanes; in modern society, people operate automobiles, trains, subways and airplanes, the apparent appearance is unfamiliar, the modern society is common, and the development and innovation space in the future is a challenge for people, so that people are struggled for accumulated work in China and the world, unmanned driving does not have human operation or robot operation, and people are not relieved, so that the invention researches and invents a novel driving technology of automobiles, trains, subways and airplanes, and robots drive automobiles, trains, subways and airplanes; operating car, train, subway and airplane operating floor equipment; the technology has the advantages that traffic accidents are reduced, traffic congestion is reduced, driving is guaranteed, and flying is stable in running, and the technology is convenient and quick to use, rapid to operate, more humanized, more practical and more relieved; is suitable for the future development situation.

Disclosure of Invention

The robot system for driving car instead of human being is composed of sensor, signal conditioning circuit, converter, computer display, data processing device, road image recognition device, transmission and power system, initialization, execution mechanism, adapter, man-machine interface, robot, alarm system, driving system, nervous system thinking, sensing network and motion system; the robot replaces a human to drive an automobile system structure and comprises a starting system, information receiving, information checking, information retransmitting, passing checking, receiving finishing, system requirement analysis, system overall design, sampling rate determination, scale conversion design, microprocessor chip selection, movement detection, vehicle identification, human face identification, hardware circuit design, hardware circuit debugging, software program design, software program debugging, software and hardware joint debugging, environment sensing, behavior prediction, planning execution, an operating system, high-precision positioning, high-precision maps, system safety, system overall performance testing, system integration and maintenance, design scheme modification, automatic driving grading calibration, analysis processing, state recognition, signal acquisition, data display, video storage, fault code recording, step correction, voice module and infrared detection, the system comprises a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS (global positioning system) positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system;

the robot replaces human driving automobile system, the robot road recognition device is installed on the robot (eyes) can 360 degree turn camera, the automobile is respectively installed with 360 degree turn camera, it recognizes front, back, left and right obstacles, the radar sensor and laser range finder analyze traffic condition, and navigate the road in front through a detailed map, all of them are realized by computer data center, like human brain, it is used to make decision, after obtaining information from the road recognition device, it is judged that the automobile is on or off, backing or deceleration, the next action most suitable for environment is selected according to the actual condition at that time, the analyst gives full analysis to each situation occasion in advance, the best group of operation parameters are inputted into the computer memory, when driving, the computer is used to make corresponding search, the left and right wheel sensors are used for positioning the position of the automobile; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection, path planning and the like, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the automobile, including traffic flow state division (such as sparse and dense), the game state of traffic participants (such as getting out of ramps), the peripheral prediction outputs the state and the track of peripheral vehicles (including bicycles, pedestrians, automobiles and trains) in a period of time in the future, and the behavior selection outputs a certain type of driving behavior (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided into parts, and modularization is easy, so that the decision algorithm is high in computability and strong in interpretability, and the implementation of a project is facilitated; the future development situation is that the layered framework and the learning method are fused, and the autonomous learning and the prior knowledge (road structure, vehicle dynamics model, driving experience and rules) are fused.

The system for driving the train by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; the robot replaces a human to drive a train system structure and comprises a starting system, information receiving, information checking, information retransmitting, passing checking, receiving finishing, system requirement analysis, system overall design, sampling rate determination, scale conversion design, microprocessor chip selection, movement detection, vehicle identification, face identification, hardware circuit design, hardware circuit debugging, software program design, software program debugging, software and hardware joint debugging, environment sensing, behavior prediction, planning execution, an operating system, high-precision positioning, high-precision maps, system safety, system overall performance testing, system integration and maintenance, design scheme modification, automatic driving grading calibration, analysis processing, state identification, signal acquisition, data display, video storage, fault code recording, step correction, voice module and infrared detection, the system comprises a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS (global positioning system) positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system;

the robot replaces human to drive the train system, install the robot road recognition device in the robot (eyes) can 360 degrees turn the camera, the train is equipped with 360 degrees turn the camera separately, discern the front and back left and right sides obstacle, radar sensor and laser range finder analyze the traffic situation, and navigate the road in front through a detailed map, this all is realized through the computer data center, like the human brain, it is used for carrying on the decision-making, after obtaining information from the road recognition device, need to make a decision, whether the train is started or stopped, the next action that the back or slows down should be according to the actual situation at that time, the analyst should give the sufficient analysis to various situation occasions in advance, input the best a series of operating parameters into the computer memory, while driving, utilize the computer to carry on the corresponding search, the left and right wheel sensors are used for positioning the train; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection, path planning and the like, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the train, including traffic flow state division (such as sparseness, denseness and the like), the game state of traffic participants (such as getting out of ramps), the peripheral prediction outputs the state and the track of peripheral vehicles (including bicycles, pedestrians, automobiles, trains and subways) in a period of time in the future, and the behavior selection outputs a certain type of driving behaviors (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, vehicle dynamics model, driving experience, rules).

The system for driving the subway by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; the robot replaces a human to drive a subway system structure and comprises a starting system, information receiving, information checking, information retransmitting, passing checking, receiving finishing, system requirement analysis, system overall design, sampling rate determination, scale conversion design, microprocessor chip selection, movement detection, vehicle identification, face identification, hardware circuit design, hardware circuit debugging, software program design, software program debugging, software and hardware joint debugging, environment sensing, behavior prediction, planning execution, an operating system, high-precision positioning, high-precision maps, system safety, system overall performance testing, system integration and maintenance, design scheme modification, automatic driving grading calibration, analysis processing, state identification, signal acquisition, data display, video storage, fault code recording, step correction, voice module and infrared detection, the system comprises a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS (global positioning system) positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system;

the robot replaces the human driving subway system, the robot road recognition device is installed on the robot (eyes) can 360 degree turn camera, the subway is respectively installed with 360 degree turn camera, it can recognize the front, back, left and right obstacles, the radar sensor and the laser range finder can analyze the traffic condition, and can utilize a detailed map to navigate the road in front, all of them are implemented by computer data center, like human brain, they are used for making decision, after the information is obtained from the road recognition device, it can make decision, the subway is started or stopped, and the next action which can be most adapted to environment can be selected according to the actual condition at that time, the analyst can give full analysis to various situations in advance, and can input the optimum group of operation parameters into the computer memory, when driving, it can utilize computer to make correspondent search, the left and right wheel sensors are used for positioning the subway position; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection, path planning and the like, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the subway, the cognition comprises the division of traffic flow states (such as sparseness, denseness and the like), the game states of traffic participants (such as getting out of ramps), the peripheral prediction outputs the states and the tracks of peripheral vehicles (including bicycles, pedestrians, automobiles, trains and subways) in a period of time in the future, and the behavior selection outputs a certain type of driving behaviors (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, vehicle dynamics model, driving experience, rules).

The system for replacing human piloting the airplane by the robot consists of a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a piloting system, a nervous system thinking, a sensing network and a motion system; the robot replaces a human piloted airplane system structure and comprises a starting system, information receiving, information checking, information retransmitting, passing checking, receiving finishing, system requirement analysis, system overall design, sampling rate determination, scale conversion design, microprocessor chip selection, movement detection, vehicle identification, human face identification, hardware circuit design, hardware circuit debugging, software program design, software program debugging, software and hardware joint debugging, environment sensing, behavior prediction, planning execution, an operating system, high-precision positioning, a high-precision map, system safety, system overall performance testing, system integration and maintenance, design scheme modification, automatic piloting grading calibration, analysis processing, state recognition, signal acquisition, data display, video storage, fault code recording, step correction, a voice module and infrared detection, the system comprises a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS (global positioning system) positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system;

the robot replaces the human piloting airplane system, the robot road recognition device is installed on the robot (eyes) can 360 degree turn camera, the airplane is respectively installed with 360 degree turn camera, the front, back, left and right obstacles are recognized, the radar sensor and the laser range finder analyze the traffic condition, and the road in front is navigated through a detailed map, all of which are realized by the computer data center, like the human brain, and are used for decision making, after the information is obtained from the road recognition device, the decision is needed to be made, the next action which is most suitable for the environment is selected according to the actual conditions at that time when the airplane is started or stopped, the airplane is backed or decelerated, the analyst gives full analysis to various situations in advance, the best group of operation parameters are input into the computer memory, and the computer is used for corresponding retrieval during flying, the left and right wheel sensors are used for positioning the airplane; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the airplane to perform task operation; the robot automatically identifies the encoded parking positions and multi-branch paths, and the robot automatically identifies the signs of acceleration, deceleration, right-angle turning, flight, stop and flight; the robot intelligently identifies obstacles; decomposing a decision-making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection, path planning and the like, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the airplane, including flight state division (such as sparseness, denseness and the like), the game state of traffic participants (such as rushing out ramps), the peripheral prediction outputs the state and the track of peripheral airplanes (including bicycles, pedestrians, automobiles, trains and subways) in a future period of time, and the behavior selection outputs a certain type of driving behaviors (such as exceeding the airplane, changing lanes, approaching, following the airplane, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided into parts, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; the future development situation is that the layered framework and the learning method are fused, and the autonomous learning and the priori knowledge (road structure, flight dynamics model, driving experience and rules) are fused.

The novel driving system for the automobile, the train, the subway and the airplane specifically comprises the following steps:

the sensor is a robot sensor and comprises a camera, a laser radar, a millimeter wave radar, an ultrasonic radar, a GPS navigation sensor, an inertial sensor, a laser range finder, a sensitive element, a conversion element and a conversion circuit.

The signal conditioning circuit is composed of a robot circuit and a signal processing circuit, converts an analog signal into a digital signal for data acquisition, processing, calculation, display and reading or other purposes, changes the type of an input signal by using internal circuits such as a filter, a converter, an amplifier and the like and outputs the signal, and in practical application, industrial signals are high voltage, overcurrent, surge and the like, cannot be correctly identified by a system, and therefore need to be adjusted and cleaned.

The converter is composed of a robot converter, an input voltage signal is converted into a current signal with a certain relation, the converted current is equivalent to a constant current source with adjustable output, and the output current of the constant current source can be kept stable and cannot change along with the change of a load.

The computer display is composed of a robot display, a liquid crystal panel, a driving board, a power panel, a high-voltage board and a key board. Displaying each instrument on a computer screen, and checking whether the value of each part is wrong. The robot display is the man-machine interface of the running system of the car, train, subway and plane, it offers the driver with the running state of the car, train, subway and plane in the form of graphic or literal information, set up the function of password protection, on these several screens, every page has fixed keys to change the page, there are keys used for reporting stops or inputting the relevant parameter.

The data processing device is composed of a robot processing device, data collection is performed periodically (generally, once in five minutes) to detect and store direct current voltage signals output by various analysis instruments and meteorological instruments, the signal processing converts the areas or heights of the direct current voltage signals output by the various analysis instruments and meteorological instruments into digital signals, the data processing calculates the numerical values of various meteorological parameters and the concentrations or contents of various measured substance components, calculates the average value per hour and the average value per day, counts the number of exceeding standards and the maximum value, the program processing is performed on the work of the composition units of the device and the analysis instruments, and the codes, the time average value, the daily average value, the number of exceeding standards and the maximum value of the recorded components and the meteorological parameters are printed.

The road image recognition device is characterized in that a camera is arranged inside or outside the system, the robot is provided with the camera, and the camera has a night vision function, a perspective function, a high-power camera shooting function, a wireless or wired transmission function, a remote transmission and watching function, an upgradable function and an automatic supervision function, and is particularly arranged on the roof of an automobile, the left side and the right side of the automobile and the front and back of the automobile; the top of the train, the left side and the right side of the train, and the front and the back of the train; the top of the subway, the left side and the right side of the subway and the front and back of the subway; the top of the airplane, the left side and the right side of the airplane, the front and the back of the airplane, and the inside or the outside of the airplane are provided with cameras.

The transmission and power system means that the robot is the trunk of an automobile, a train, a subway and an airplane, and is already a part at the beginning of design. Whether as a conventional internal combustion engine, electric engine, or hybrid engine, the portion of the powertrain in this field can convert raw fuel into power, which typically includes a robotic engine, a gearbox, drive shafts, axles, and wheels.

The initialization is formed by robot initialization, namely factory setting, maintenance or repair, initialization operation is carried out on a part of the maintained assembly system to ensure that each system can work normally, and automatic calculation and adjustment are carried out through a system chip. The console computer is initialized and then repaired by the repair instrument or the robot, the repair instrument is initialized and then the robot is repaired, and the robot is initialized and then the repair instrument is repaired.

The executing mechanism is composed of a robot executing mechanism, is a common electromechanical integrated device in the field of automatic processing, is three major components (detection equipment, adjusting equipment and executing equipment) of an automatic instrument, and is used for adjusting and processing various automatic equipment and system moving parts in various forms, so that the robot can still normally work under the conditions of power failure, gas failure, no output of a regulator or failure due to damage of the executing mechanism. The staff realizes replacing the human ear to actuating mechanism robot, can discern the instruction that the speaker assigned through speech processing and recognition technology.

The adapter consists of a robot adapter, a switching circuit, a voltage transformation circuit and an output circuit. The adapter is internally provided with an over-short circuit protection, and the adapter can automatically protect when the load is short-circuited or the load is too heavy.

The man-machine interface is composed of a robot man-machine interface, a man-machine interface device, an interaction technology, a monitoring technology, a remote operation technology and a communication technology. The input and output interface is a connection interface between the computer and the man-machine interaction equipment, and information exchange between the computer and the peripheral equipment can be realized through the interface. The robot circuit and the signal are transmitted in a wireless or wired mode, and charging can be achieved in a wired or wireless mode.

The robot is composed of an industrial robot, a programmer, a robot claw, positioning equipment and robot software, the robot is provided with a walking mechanism, the robot hand can be provided with two fingers or multiple fingers, and the robot can be a paint spray gun, a welding gun, a laser gun and a robot capable of lifting, can automatically translate and automatically recognize languages.

The alarm system is composed of a robot alarm system, an electric infrared sensing module, an electric infrared remote control transmitting circuit, a receiving circuit and a signal processing module, and can realize digital anti-theft, communication anti-theft, image anti-theft, fault alarm and networking alarm.

The driving system refers to the key problems to be solved in terms of switching of the driving right of the robot, namely, the switching time and the influence of switching on a driver. The execution right rigid connection can be carried out by judging the gripping degree of the steering wheel by the robot in the aspect of switching the execution time. In terms of the influence of the switching execution on the robot, the participation in the non-driving task may cause a reduction in the robot perception and the capability of scene reconstruction. And the analysis is carried out from the perspective of driving weight fusion, and key problems such as human-computer interaction and driving weight distribution problem, strategy, test evaluation method and the like need to be considered emphatically. Initially the way in which the weights between the human driver and the robot were studied. Abuse is considered to weaken the driving ability of the human robot, and a haptic interactive man-machine execution strategy for promoting the improvement of the driving ability of the robot is provided.

The neural system thinking means that the robot automatic driving system is a comprehensive system integrating a plurality of high and new technologies, and environment information acquisition and intelligent decision execution which are taken as key links depend on innovation and breakthrough of a series of high and new technologies such as a sensor technology, an image recognition technology, an electronic and computer technology and an execution technology. The robot unmanned automobile is expected to have great development and depends on the breakthrough and innovation of various technologies. The key technologies related to the robot automatic driving system comprise environment perception, logical reasoning and decision, motion execution, processor performance and the like. With the progress of machine vision (such as a 3D camera), pattern recognition software (such as an optical character recognition program), and a light system (which has combined global positioning technology and spatial data), a robot in-vehicle computer can perform automobile, train, subway, and airplane traveling by combining machine vision, sensed data, and spatial data. The popularization of the vehicle-mounted intelligent traffic lane system also has some key technical problems to be solved, including the communication protocol specification among vehicles, the problem that unmanned vehicles share the traffic lane, the establishment of a general software development platform, the information fusion among various sensors and the adaptability of a visual algorithm to the environment. The robot driver replacement products can be said to be the brains of cars, trains, subways, and airplanes. Also, it can take full advantage of new knowledge gained from experience, just like the human brain. One way for robots to autopilot cars, trains, subways, and airplanes is to use cloud connectivity. For example, when a robot autopilot is parked in a garage at night, for example, in a car, train, subway, and airplane, it can connect to the cloud and upload data accumulated during the day. These data can be integrated with other vehicle, aircraft data for optimizing the driving algorithm. The new functions can be downloaded by "sleeping" cars, trains, subways, and planes so that when it "wakes up" in the morning, it can be turned on for a new day using the new functions.

The perception network means that the robot operates similar to the human brain, and data perceived by the automatic driving sensor can form driving situation graph clusters at intervals to form the working memory of the robot; the long-term memory comprises a driving map and various driving prior knowledge; the motivation is a certain path requirement for intelligent driving, and can be communicated to the robot through human-computer interaction. Through the interaction of short-term memory, long-term memory and motivation, the robot forms an autonomous decision, transmits an execution instruction to an execution mechanism, and completes the whole automatic driving process. The technical system of autonomous driving is as follows, based on the robot architecture, it is possible to connect each other through a communication network, allowing each to operate with serial and shared information. As an adhesive to bring together the various domains in the architecture, the internal network can ensure that data is shared in a secure and reliable manner within the appropriate bandwidth. The internal network employs many of the same technologies in today's most advanced IT domain, including ethernet connections and security gateways. Networks (IVNs), including various conventional technologies such as CAN, LIN, and ethernet, CAN securely connect the various domains without concern. The IVN allows the individuals to share relevant information, and the robot gateway ensures the correct distribution of data. The gateway will keep the information in, protecting it from external access and external attacks. The gateway is used for protecting the subsystems (constructing a firewall), and isolating each subsystem to avoid accidental interaction. In this way, the safety critical system can be isolated from the operation of other systems, such as infotainment systems. The gateway may also ensure that large amounts of data for each use can be efficiently and reliably transmitted. The networking system is a dynamic mobile communication system for realizing interaction between automobiles, trains, subways, airplanes and automobiles, trains, subways, airplanes and people, automobiles, trains, subways, airplanes and cloud terminals and the like and realizing communication between the automobiles, the trains, the subways and the airplanes and the public network. The robot can realize information sharing through interconnection and intercommunication, collect information of vehicles, environments, roads and flights, process, calculate and share the information on an information network platform, and is applied to automatic driving of the robot.

The motion system refers to that a robot drives an automobile, a train, a subway and an airplane, has the functions of automatically waking up and starting up and sleeping, automatically entering and exiting a parking lot and stopping an airport, automatically cleaning, automatically driving, automatically stopping, automatically opening and closing a vehicle door and automatically recovering from faults, and has various motion modes such as normal operation, degraded operation, operation interruption and the like.

The starting system is characterized in that the robot is used as a vehicle, a train, a subway and an airplane to run and start, perform tasks and automatically and manually start each starting system.

The received information refers to the functions of an intelligent instrument (a robot screen) and a robot receiving and communicating system, data transmission, passwords, data compression, professional knowledge voice question answering, picture presentation and video playing. And (3) configuring a repairing instrument and a robot (note that the mobile phone and the computer can be configured).

The verification information refers to that an intelligent instrument (a robot screen) and a robot need to use an intelligent card chip, a password or a digital certificate can be stored, a one-time authentication mode is required, a dynamic password is also required, a mobile phone verification code needs to be input for 60 seconds, the user face recognition is carried out, face recognition is carried out based on face feature information of the user, each user is accurately corresponded, and services are provided for user personalization, identity confirmation and the like. The user can pass this final authentication mode.

The resending means that the information can be resent for five times when being sent, and if the information is still wrong, the intelligent instrument (a robot screen) and the robot are automatically locked and need to be initialized and restarted.

The verification is passed when the information is sent, and the intelligent instrument (robot screen) and the robot start to start. Character function, Chinese and English mode.

The receiving is finished by an intelligent instrument (a robot screen) and a robot intelligent card, and the intelligent instrument is automatically started after the mobile phone verification code is received.

The system requirement analysis refers to the analysis of the requirement of a robot system, and is used for revealing, analyzing and distributing expected running functions of automobiles, trains, subways and airplanes to each individual system element.

The overall design of the system is that the overall structure of the robot system is designed firstly, and then the robot system goes deep layer by layer until each module is designed, and the overall design mainly refers to the overall design of the system on the basis of system analysis, in the aspects of the division (subsystems) of the operation of the whole automobile, train, subway and airplane, the configuration of machine equipment (including soft and hard equipment), the storage rule of data, the implementation planning of the operation of the whole automobile, train, subway and airplane and the like.

The sampling rate determination refers to the determination of the sampling rate of the robot, and the sampling speed, also called the digitization rate, is carried out on the input signals in the running of automobiles, trains, subways and airplanes.

The scale conversion design refers to a robot scale conversion design, in the operation of automobiles, trains, subways and airplanes, all parameters in operation have different values and temperatures, and for further operations such as display, record, alarm and the like, the digital values are converted into different units so that an operator robot can monitor and process the operation process, namely the scale conversion.

The selection microprocessor chip is a robot selection microprocessor chip, is a complete calculation frequency-guiding, automobile, train, subway and airplane operation microprocessor chip assembled on a single chip, can complete the operations of obtaining instructions, executing instructions, exchanging information with an external memory and a logic component and the like, is an operation center part of a computer, and can form a microcomputer together with the memory and a peripheral circuit chip.

The mobile detection refers to the itinerant detection of an intelligent instrument (a robot screen) and a robot camera. The mobile detection is commonly used for unattended monitoring video recording and automatic alarm, and the robot can identify image change in a designated area, so that corresponding processing and alarm information pushing can be rapidly carried out. By enabling the solution of intelligent AI + IPC, the IPC equipment has a mobile detection function and utilizes the AI capability to make the alarm more accurate and timely and enable the owner to process the alarm information at the first time. In the future, the robot IPC equipment with the mobile detection function can further improve the monitoring/protection system, for example, in an infant monitoring system, if an adult makes coffee or does not cook for a baby around the baby, the baby climbs to an area easy to fall, and the robot IPC equipment with the mobile detection function can detect that the baby is in danger and timely pushes alarm information, so that the robot can rapidly protect the safety of the baby. In future home or enterprise anti-theft systems, when the picture changes, if people walk, the lens is moved, the robot IPC equipment can detect abnormal conditions in time and send alarm messages in time so as to prevent the property of the individual or enterprise from being stolen and ensure that the safety protection is extremely safe.

The vehicle identification means that the robot is likely to be as common as a mobile phone by performing technological innovation and evolution in the future, people can own the robot, and the safety problem of the robot becomes a popular topic. By means of the vehicle identification technology, the safety of automobiles, trains, subways and airplanes can be further protected; for example, the vehicle is parked in a yard, the state of the vehicle is monitored, and once abnormal information of the vehicle is found, the abnormal information is timely provided to the robot, so that the vehicle is protected from being stolen. Compared with family life, the requirement of the intelligent society on the popularization of vehicle identification in the future is more urgent. No matter the intelligent parking service of the intelligent community or the intelligent traffic system of the intelligent city, the intelligent IPC solution can provide AI capability and enable a security scene through the technology. For example, accurate vehicle access identification, payment system, parking space condition statistics and the like are provided in an intelligent community, and in an intelligent traffic system, more professional services such as traffic jam condition, traffic accident judgment, criminal vehicle tracking and the like can be provided for a decision-making department.

The face recognition refers to robot face recognition, and is commonly applied to face unlocking and face payment on a mobile phone. On IPC equipment, the intelligent face recognition technology is more applied to a security access control system; can also be applied to robot equipment; for example, in the future, in our family life, the entrance guard applying face recognition will certainly become the mainstream, and replace the traditional entrance guard to greatly increase the family safety. On the basis of the face recognition technology, the identification accuracy of the access control system can be further improved through a more professional living body detection technology. Even if the door is brushed by a twin, the door can be detected by brushing the photo. In enterprise application, the entrance guard system applying face recognition is the best entrance of future smart enterprises, smart communities and even smart cities, and intelligent energized IPC equipment can perfectly solve practical problems and is further applied and promoted.

The hardware circuit design refers to the automation of robot hardware circuit design, and the automation of automobile, train, subway and airplane operation electronic circuit design is realized by taking a computer as a working platform, taking a hardware description language as a design language, taking a programmable program as an experiment carrier and taking a chip as a core to perform element modeling and the automatic design process of an automobile, train, subway and airplane operation system, and performing scheme design and function division on the whole automobile, train, subway and airplane operation. The hardware part comprises a binocular camera device, an image processing platform, a software library, an execution interface, an execution mechanism and the like.

The hardware circuit debugging refers to the debugging of a robot hardware circuit, and the debugging of the hardware circuit of an automobile, a train, a subway and an airplane running system finds and corrects the deficiency of a design scheme through the test and adjustment after installation, and then measures are taken to improve so that the hardware circuit debugging reaches the preset technical index.

The software programming refers to robot software programming, ground identification, isolation zones, anti-collision guardrails, lane identification line recognition, roadblocks, the number of motor vehicles and lanes, and flight analysis system software automatically decides the running speed, the running direction and the position of automobiles, trains, subways and airplanes, over-speed driving, emergency braking, stopping flying, whistling, lighting and the like according to the information.

The software program debugging refers to the debugging, testing and adjusting of the robot software program, the discovery and correction of the defects of the design scheme, and then the improvement of measures are taken, wherein the software part mainly comprises the aspects of target identification, motion parameter measurement, image processing and the like. The image processing platform performs primary recognition on the left image and the right image by using image processing software according to a standard road model of the knowledge base, and divides a travel road area.

The software and hardware combined debugging refers to the robot software and hardware combined debugging, and the software and hardware are matched with and associated with each part, so that the software and hardware can be stably matched and used. Robots that automatically steer cars, trains, subways, and planes do not have common hardware and common operating systems. Although chip companies and internet companies have a ambition in this respect. The robot automatic driving software service is an application-level automatic driving auxiliary software service for automobile, train, subway and airplane enterprises, including perception, self-positioning and decision-making. The man-machine interaction product is based on a basic structure and data acquisition capacity of a map, the advantages of the map, navigation, private cloud, voice and safety products are fully utilized, and a more perfect man-machine interaction service platform, which is a more perfect man-machine interaction service platform, is built for a master, and comprises a man-machine interaction service platform, a robot-machine interaction service platform, a subway interaction service platform, a robot-machine interaction service platform, a subway interaction service platform. For better user experience, the robot automatic driving system mainly comprises two parts, namely hardware and software.

The monitoring operation refers to an intelligent instrument (a robot screen) and a robot, and workers need to monitor, protect and operate anytime and anywhere in the test stage.

The environmental perception means that the robot carries out 3D reconstruction on the dynamic and static objects around the vehicle body by using the sensor suite. At present, the environment perception technology has two technical routes, one is a multi-sensor fusion scheme taking a camera as a leading factor; the other technical scheme takes laser radar as a main part and other sensors as auxiliary parts.

The behavior prediction means that the robot automatic driving perception system needs to realize rapid, accurate and reliable environmental behavior prediction under the conditions of complex terrain, complex weather (weather such as rain, snow, fog and the like) and complex road traffic environment.

The planning execution refers to that the robot automatically drives the automobile, the train, the subway and the airplane to conduct information processing according to the robot environment perception and navigation subsystem and by combining a given starting point and a given end point with a path planning system. Currently, specialized chip/computing platforms for robotic autopilot decision-making and planning include the intel development series. The execution platform is an unmanned core component and executes various execution systems. The execution system can be divided into two links of longitudinal execution (the robot adopts an accelerator and executes a comprehensive execution method to track a preset speed) and transverse execution (including simulation of the robot behavior of a driver and analysis of dynamics).

The operating system refers to a robot-driven automobile system which can operate an automobile navigation system, an air bag system, a defrosting device, a combination instrument, a steering column cover, a brake pedal, a pedal, an accelerator pedal, a steering wheel, a parking gear system, an air lifting device, a loudspeaker, a camera, an automobile side warning system, an off-lane warning system, a brake auxiliary system, a parking auxiliary system, an adaptive cruise system, an automatic parking system, an anti-collision system, a blind spot detection system, an automobile radar system, an auxiliary lane changing system, an air conditioner system, a GPS positioning device and a computer system; the robot driving train system can operate an automatic train running execution system, a computer network, a monitoring device, a temporary speed limiting server, a locomotive signal server, a transponder, a vehicle-mounted device, a combination instrument, an air conditioning system, a camera, a lane deviation warning system, an adaptive cruise system, an automatic parking system, an anti-collision system, a blind spot detection system, a train radar system, an auxiliary lane changing system, an automatic train protection system, an automatic train driving system, an automatic train monitoring system, a GPS positioning device and a computer system; the robot driving subway system can operate a subway operation execution system, a computer network, a monitoring device, a temporary speed limit server, a subway signal server, a transponder, subway vehicle-mounted equipment, a combination instrument, an air conditioning system, a camera, a lane deviation warning system, an adaptive cruise system, an automatic parking system, an anti-collision system, a blind spot detection system, a subway radar system, an auxiliary lane changing system, a subway automatic protection system, a subway automatic driving system, a subway automatic monitoring system, a GPS positioning device and a computer system; the piloted robot aircraft system can operate an aircraft operation execution system, a computer network, a monitoring device, a temporary speed limit server, an aircraft signal server, a high-frequency system, a very high-frequency system, a combination instrument, an air conditioning system, a camera, an adaptive cruise system, an automatic stop-flight system, an anti-collision system, a blind spot detection system, an aircraft radar system, an auxiliary transformation flight system, an aircraft automatic protection system, an aircraft automatic piloting system, an aircraft automatic supervision system, a GPS positioning device and a computer system.

The high-precision positioning is that data acquired by the robot finger laser range finder and GPS data can be gathered and integrated in a computer, and the flight path is corrected in real time, so that the line precision can be greatly improved, and the error of a navigation system is reduced to a centimeter level. While laser sensors can discriminate between other vehicles, pedestrians, bicycles, and other large and small stationary objects, and do not emit light visible to the naked eye, they still require radar assistance in their ability to detect high-speed moving objects at great distances. The positioning technology is used for guiding the positioning position of an automobile, a train, a subway and an airplane as the name implies, and relates to an inertial navigation system, a left wheel speed encoder, a right wheel speed encoder, a track calculation, a satellite navigation system and an SLAM autonomous navigation system.

The high-precision map refers to a robot map difference method, which is to analyze the distribution of obstacles according to the states of different obstacles on the map at different moments to obtain motion information. There is an article that proposes a real-time detection method for dynamic and static obstacles based on spatio-temporal correlation attributes in a dynamic environment. The readings of the environment perception sensors at different moments are uniformly converted into a world coordinate system, and the dynamic obstacles and the static obstacles can be identified by analyzing the time attributes and the space attributes of the obstacles. The method does not need to map the sensor reading to a grid map, saves storage and calculation time, and improves obstacle identification efficiency. The robot physical aggregation method classifies data collected by a laser radar, collects entity information of moving obstacles according to classification, and describes some states of the obstacle entity information by forming the state information of each obstacle entity by information in a plurality of categories. The robot tracking method refers to tracking a trajectory of an obstacle to obtain motion information. Due to the relevance of multi-target environment data and the inevitable error of the laser radar sensor, the relevance of targets at different moments needs to be discussed according to situations in a classified mode. In order to better avoid potential risks and help to predict road surface information such as gradient, curvature, course and the like, the unmanned robot is often required to be combined with a real-time high-precision map, and the real-time performance can be realized through networking, and the map is updated at any time and any place.

The system safety means that a robot driver replaces a product to allow a robot to take over a driving task. It provides the perception and inspiration functions and ensures correct operation with a assurance system. The driver replacement product domain is a lot of "intelligence" that can resolve environmental conditions detected by various sensors and cameras. "sensory" components include radar, camera, laser-based, and components for locating and detecting other environmental information. The "thinking" component contains environment assessment, route planning, sensor fusion, safety-related algorithms. At present, when driving an automatic transmission automobile, basically two pedals of an accelerator and a brake are executed by adjusting a steering wheel. Regardless of the scale used, however, the robot driver is superior to our human in these operations. The robot driver can react faster and more continuously, is not affected by human emotions, and is always in a pre-warning state. It also does not drink coffee, eat snacks, or have other distracting activities at work.

The system overall performance test means that the overall performance test of a robot system, the operation overall performance test of an automobile, a train, a subway and an airplane decomposes the system into a plurality of functional units which are organically connected with each other, the functional units are taken as subsystems to be decomposed continuously until a technical scheme is found, and then the functions and the technical scheme are combined to be analyzed, evaluated and optimized to synthesize scientific and technological technology.

The system integration and maintenance means that the robot system integration and maintenance, the integration and maintenance of automobiles, trains, subways and airplane operation systems are realized by integrating various separated equipment computers, functions, information and the like into a mutual correlation, unification and coordination system through a structured comprehensive wiring system and a computer network technology, so that the robots are fully shared, the centralized, efficient and convenient detection is realized, the equipment is maintained at regular intervals, the maintenance comprises line inspection, equipment operation condition inspection and computer equipment disk cleaning, and the software test platform is programmed and tested to modify or download and update.

The modification design scheme refers to a robot modification design scheme, and a part of maintenance items are modified by the operation modification design scheme of automobiles, trains, subways and airplanes, so that the occurrence of faults is reduced, and the reliability of system components is improved. This can manage motion and speed, the robot autopilot moves based on information input by the driver or the driver-replacement product robot, and can be modified and optimized based on personal preferences and environmental constraints (e.g., road conditions).

The automatic driving classification standard means that a human driver operates an automobile, a train, a subway and an airplane at all times without automatic driving, and can be assisted by a warning and protection system during the running process. Currently there are no driving-assisted vehicles that are considered to possibly contain some active safety devices. The driving support provides driving support for one of the steering wheel and acceleration/deceleration by the driving environment information, and the other driving operations are performed by the human driver. Currently, the assisted driving technologies such as road maintenance, cruise control, ACC adaptive cruise and ESP are different in overall comfort. The partial automation provides driving support for multiple operations in a steering wheel and acceleration and deceleration through driving environment information, other driving operations are completed by a human driver, an automatic driving system exceeding the capability gives an execution right to a robot, and the human driver needs to monitor in real time and take over preparation. The most obvious difference is whether the system can be implemented in both the lateral and longitudinal directions of the vehicle. The conditional automation provides driving support for a plurality of operations in steering and acceleration/deceleration by driving environment information, and other driving operations are performed by a human driver. Conditional autopilot refers to the situation where a robot is automatically driven in certain specific scenes (highway/road congestion, etc.), and a human driver still needs to monitor driving activities. It is now the focus of research and development. The full-time driving operation is completed by the robot unmanned system in a high degree of automation, and according to system requests, human drivers do not necessarily need to respond to all the system requests, so that road and environmental conditions are limited. The vehicle is not mature, and related vehicle types are few; is expected to be the focus of research and development. The accuracy and precision of the robot autopilot algorithm needs to reach or even exceed the cognitive level of human beings, which requires an extremely robust algorithm and a stable computing platform. The high-precision sensor (laser radar and the like) and the automatic driving execution chip used in the automatic driving are extremely expensive at present, and have a considerable distance from popularization. Some automation can be robotic unmanned cars, trains, subways, and planes, allowing all occupants to engage in other activities without the need for a monitoring system. This level of automation allows activities such as computer work, rest and sleep, and other entertainment. After the popularization, the major changes will occur in the industry for one hundred years, and the travel mode of people will change greatly.

The analysis processing refers to that an intelligent instrument (a robot screen) and a robot monitor and capture the images outside or inside each system by a camera, and the images are shot, so that the road condition in front of the analysis processing is directly displayed and analyzed.

The state identification refers to that an intelligent instrument (a robot screen) and a robot operate an automobile, a train, a subway and an airplane to identify the relevant state of mechanical equipment according to the operation information of the mechanical equipment. The state monitoring is an important technical means for improving the operation reliability, safety and product quality of equipment and reducing the maintenance cost in production and use, and the state identification monitoring opens up a new way for improving the reliability and maintainability of a system.

The signal acquisition means that an intelligent instrument (a robot screen) and a robot digitize, i.e. sample or quantize, a measured signal in a digital storage oscilloscope, and then the measured signal can be stored and displayed.

The data display means that the intelligent instrument (robot screen) and the robot can output the data in the internal or external memory of the system in a visible or readable form, and has the forms of data value direct display, data table display, various statistical graphic displays and the like, the digital display is the most basic output mode of the intelligent instrument, and the commonly used display comprises a light emitting diode, an LED nixie tube and a touch LCD.

The video storage refers to that an intelligent instrument (a robot screen) and each node of a robot are internally provided with an independent solid state disk, and each solid state disk has limited space, so that in order to exert the advantages of virtual storage, a plurality of or dozens of storage nodes are subjected to virtual management through storage aggregation to form a large storage pool, and the surface of storage system equipment is automatically cleaned and maintained every three months, and automatic power failure maintenance is performed once in a half year by a plurality of technical means such as virus immunity, network link redundancy, power supply, fan redundancy, network fault initialization, system image backup and the like.

The fault code recording means that the fault codes are classified into high, medium and low levels by an intelligent instrument (a robot screen) and a robot, and the fault codes are recorded and displayed on each screen.

The step correction means that all parts of a walking body of a robot are in a coordination relationship in time sequence and space in the walking process, the movement of the parts depends on the inconsistent rotation speed of a motor or the step is disturbed in the steering process, the step correction function is started at this time, the steps are disturbed by a blocking piece in the rotation speed of the motor, the steps need to be corrected, at this time, the next leg can be stopped at random, and the other leg walks at a proper position and then synchronously moves forward.

The voice module means that the robot mainly adopts the most advanced simulation recording technology in the world, the whole language capability is completed by integrating a simulation recording chip, and a thinking analysis chip illustrates that for example, an article can be analyzed and read out and can analyze the judgment of the road in front of driving from the article.

The infrared detection means that the robot utilizes an infrared emission sensor, ultrasonic waves or microwaves and radar technology to send infrared signals to sense a front object, a front object unit is screened out through a corresponding software program, infrared scanning is carried out on a fault object, how much damage the fault object is damaged is detected, and avoidance is carried out according to the condition.

The ground detection means that the robot always receives ground feedback signals, and once the ground feedback signals cannot be detected, another walking state can be executed. For example, contact with a water path, water path travel, contact with an oil path, and oil path travel.

The drive circuit means that the transmission device and the transmission circuit are required to be freely arranged for each joint, namely the movement, when the robot moves the joints.

The photoelectric conversion is a robot rotating speed optical signal conversion device which is used for converting chemical reaction generated by identifying a measured object on a functional film into an electric signal or an optical signal which is convenient to transmit.

The touch module is realized by using collision type induction, when a robot tracks a fixed target, the touch module is triggered, and after receiving a signal, the distance of a half meter or a meter to an obstacle is kept.

The display module is used for automatically displaying the road traffic conditions of the front, the back, the left and the right when the robot operates as an automobile, a train, a subway and an airplane, and can display by screens, multiple screens and a touch screen.

The central processing unit is that the robot loads the chip on their brains, further promotes intellectuality in the aspects such as cognitive study, automatic driving, comprehensive processing to fuzzy information. It is responsible for executing various processing instructions, and the brain chip and central processor can be updated, and can be equipped with new program.

The mechanical structure system is characterized in that the robot consists of a base, a repair machine table and a repair support, a lifting rotating mechanism, an arm, an operator, a programmer, a robot paw, a positioning device and robot software are arranged between the base and the machine table, the robot is provided with a walking mechanism, the robot hand can be provided with two fingers or more fingers, and can also be a paint spray gun, a welding gun, a laser gun and a robot capable of lifting.

The sensing system is characterized in that the robot consists of an internal sensor and an external sensor module and acquires meaningful information in driving of an external or internal environment state.

The robot environment exchange system is a system for realizing the mutual connection and coordination between the robot and equipment in the external environment, and is integrated with the external equipment into a driving unit.

The man-machine exchange system refers to a robot and staff contact and participate in a robot driving instruction device, an instruction giving device and an information display device.

The information processing system is characterized in that the robot processes and integrates from the perspective of multi-information to obtain the internal connection and rules of various information, eliminates useless and wrong information, retains correct and useful components, and finally realizes the driving optimization of the information.

The timing system is used for determining how much time is needed for the robot to complete a task, the time is urgent, and serious accidents are caused by delay time, so that the task time is set to be five minutes, ten minutes, fifteen minutes, half an hour, one hour, and ten hours, and only rescue can be requested if the task cannot be completed. The self-checking is performed for one to five times in one month.

The vision module is a robot which adopts a camera shooting function to analyze and process an external object, has a structure and a built-in analysis and processing chip, is close to human eyes for judgment, obtains a digital image from a three-dimensional object through an image sensor, extracts digital image characteristics after the preprocessing of a 3D camera technical image, and finally carries out image recognition driving.

The GPS positioning is an absolute pose estimation method based on a robot GPS positioning method. The method performs positioning through a global positioning system. Magnetic induction positioning the magnetic induction positioning method based on the magnetic sensor can realize positioning by detecting the position of a magnetic signal in the unmanned driving process of the robot by installing a magnetic nail on a road. The magnetic induction positioning method has the advantages that the magnetic material is processed in advance, the detection result is stable and reliable, and the influence of illumination, weather or other obstacles can not be caused; the method has the defects of high cost and inconvenience for large-scale popularization because roads need to be reformed, and is suitable for automatic logistics guidance of airports, factories, workshops and the like. Inertial positioning an inertial sensor-based positioning method measures angular acceleration and linear acceleration by using a gyroscope and an accelerometer sensor, and integrates the measured data, thereby calculating current pose information relative to an initial pose. The inertial positioning method has the advantages that external signals do not need to be received, and the interference of the environment is small; the disadvantage is that there is an accumulated error and increases with time. Therefore, the method is suitable for positioning or auxiliary positioning in local short time. The map information matching method based on vision or laser matching and positioning through a camera or a laser radar is also an absolute pose estimation method. According to the method, map information is established in advance, and detected data characteristics are continuously compared and matched with the map information in the unmanned process of the robot, so that the absolute pose in the map is obtained. The map information based matching positioning method has the advantages that no accumulated error exists, and a road does not need to be reformed; the method has the disadvantages that the method comprises two steps of map generation and map matching, the map generation needs to be collected in advance, the data volume of the map is huge in an outdoor scene, and great challenges are brought to the real-time performance of the map matching, so that the map is required to be updated at any time.

The networking automatic driving means that the robot networking automatic driving is a product integrating automatic driving and networking technologies. By introducing modern communication and network technologies, the networking automatic driving can be in real-time communication with other communication terminals (including road side facilities, vehicles, pedestrians, automobiles, trains, subways, airplanes, other road users and the like) and a cloud end, so that information exchange and sharing of the whole traffic system are realized, perception, decision and execution capabilities are effectively expanded, and the performance of the traffic system is improved.

The moving obstacle detection means that the robot detects moving obstacles in the environment in the moving process and is mainly completed by an environment sensing system. (obviously, from a general knowledge perspective, the first step in avoiding an obstacle is to detect the obstacle)

The moving obstacle collision track prediction means that the robot carries out possibility rating and prediction on obstacles possibly encountered in the moving process, and judges the collision relation with unmanned driving. (when you detect an obstacle you must let the machine judge if you will collide)

The obstacle avoidance of the moving obstacle means that the robot drives the robot to safely avoid the obstacle through intelligent decision and path planning, and the decision is executed by a path decision system. (after judging the obstacle which may collide, you have to make the robot make a decision to avoid the obstacle)

The shutdown system means that the robot is started as an automatic shutdown system when the tasks of the automobile, the train, the subway and the airplane are completed.

The invention has the advantages of the creation design: the novel driving system for the automobile, the train, the subway and the airplane can reduce traffic accidents and traffic jam, the robot can automatically find out the fault for automatic repair, and the robot driver is more excellent than human beings in the operations. The robot driver can make a response faster and more continuously, is not influenced by human emotion, and is always in an early warning state. It also does not drink coffee, eat snacks, or have other distracting activities at work. For the future, most companies believe that most links are likely to be replaced by future intelligent robots in one day after the end, and people only do some creative design and maintenance work, so that the industry of the future intelligent robots is quite likely to be the most suitable for at least hundreds of years in the future.

Drawings

FIG. 1 is a schematic view of the novel driving system of the present invention;

FIG. 2 is a schematic diagram of the novel train driving system of the present invention;

FIG. 3 is a schematic view of the novel driving system of the subway of the invention;

fig. 4 is a schematic diagram of the novel piloting system of the airplane.

Detailed Description

The embodiments are further described below in conjunction with the attached drawings and figures:

FIG. 1 is a schematic view of the novel driving system of the present invention; 1. the system for driving the automobile by the robot instead of human beings consists of a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a perception network and a motion system; 2. the robot replaces human driving automobile system structure and comprises a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction and a voice module, the system comprises an infrared detection system, a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processor, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system.

FIG. 2 is a schematic diagram of the novel train driving system of the present invention; 3. the system for driving the train by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; 4. the robot replaces human to drive the train system structure and is composed of a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment perception, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving classification standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction and a voice module, the system comprises an infrared detection system, a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processor, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system.

FIG. 3 is a schematic view of the novel driving system of the subway of the invention; 5. the system for driving the subway by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; 6. the robot replaces human to drive the subway system structure and comprises a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction and a voice module, the system comprises an infrared detection system, a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processor, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system.

FIG. 4 is a schematic view of the novel piloting system of the aircraft of the present invention; 7. the system for replacing human piloting the airplane by the robot consists of a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a piloting system, a nervous system thinking, a sensing network and a motion system; 8. the robot replaces a human piloted airplane system structure and comprises a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale transformation design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic piloting grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction and a voice module, the system comprises an infrared detection system, a ground detection system, a driving circuit, a photoelectric conversion system, a touch module, a display module, a central processor, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, a GPS positioning system, an internet automatic driving system, a moving obstacle detection system, a moving obstacle collision track prediction system, a moving obstacle avoidance system and a shutdown system.

Claims

1. A novel driving system of an automobile; is characterized in that: a robot drives an automobile system instead of a human; comprises the following steps:

the robot system for driving car instead of human being is composed of sensor, signal conditioning circuit, converter, computer display, data processing device, road image recognition device, transmission and power system, initialization, execution mechanism, adapter, man-machine interface, robot, alarm system, driving system, nervous system thinking, sensing network and motion system; the robot replaces human driving automobile system structure and comprises a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction, a voice module, an infrared detection and a ground detection, the system comprises a driving circuit, a photoelectric conversion device, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, GPS positioning, internet automatic driving, moving obstacle detection, moving obstacle collision track prediction, moving obstacle avoidance and shutdown system;

the robot replaces human to drive the automobile system, the robot road recognition device is arranged on a camera capable of turning 360 degrees of the robot (eyes), the automobile is respectively provided with the camera capable of turning 360 degrees, the front, back, left and right obstacles are recognized, the radar sensor and the laser range finder analyze the traffic condition, and the navigation of the road ahead is carried out through a detailed map, which is realized through a computer data center, like the human brain, is used to make decision, after obtaining information from the road recognition device, it is necessary to make a decision that the vehicle is on or off, backward or deceleration, and to select the next action most suitable for the environment according to the actual situation at that time, the analyst gives a sufficient analysis in advance for each situation, the best set of operating parameters is inputted into the computer memory, when the automobile is driven, a computer is used for carrying out corresponding retrieval, and the left wheel sensor and the right wheel sensor are used for positioning the automobile position; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection and path planning, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the automobile, including traffic flow state division (such as sparseness and denseness), the game state of traffic participants (such as rush out ramps), the peripheral prediction outputs the state and the track of peripheral vehicles (including bicycles, pedestrians, automobiles and trains) in a period of time in the future, and the behavior selection outputs a certain type of driving behavior (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, vehicle dynamics model, driving experience, rules).

2. A novel train driving system; is characterized in that: the robot replaces human to drive the train system; comprises the following steps:

the system for driving the train by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; the robot replaces human to drive the train system structure and is composed of a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving classification standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction, a voice module, an infrared detection and a ground detection, the system comprises a driving circuit, a photoelectric conversion device, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, GPS positioning, internet automatic driving, moving obstacle detection, moving obstacle collision track prediction, moving obstacle avoidance and shutdown system;

the robot replaces human to drive the train system, the robot road recognition device is arranged on a camera capable of turning 360 degrees of the robot (eyes), the train is respectively provided with the camera capable of turning 360 degrees to recognize obstacles at the front, the back, the left and the right, the radar sensor and the laser range finder analyze the traffic condition, and the navigation of the road ahead is carried out through a detailed map, which is realized through a computer data center, like the human brain, is used for making judgment decision, after obtaining information from the road recognition device, the judgment is made, whether the train is on or off, and whether the train is backing or decelerating is based on the actual situation at that time, the analyst needs to fully analyze the situation in advance, input the optimal set of operation parameters into the computer memory, when the train runs, a computer is used for carrying out corresponding retrieval, and the left wheel sensor and the right wheel sensor are used for positioning the position of the train; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision-making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection and path planning, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the train, including traffic flow state division (such as sparseness and denseness), the game state of traffic participants (such as rush out ramps), the peripheral prediction outputs the state and the track of peripheral vehicles (including bicycles, pedestrians, automobiles, trains and subways) in a future period of time, and the behavior selection outputs a certain type of driving behaviors (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, vehicle dynamics model, driving experience, rules).

3. A novel driving system for subway; is characterized in that: the robot replaces human beings to drive a subway system; comprises the following steps:

the system for driving the subway by the robot instead of human comprises a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a driving system, a nervous system thinking, a sensing network and a motion system; the robot replaces human to drive the subway system structure and comprises a starting system, a receiving information, a checking information, a retransmission, a checking pass, a receiving completion, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic driving grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction, a voice module, an infrared detection and a ground detection, the system comprises a driving circuit, a photoelectric conversion device, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, GPS positioning, internet automatic driving, moving obstacle detection, moving obstacle collision track prediction, moving obstacle avoidance and shutdown system;

the robot replaces human to drive the subway system, the robot road recognition device is arranged on a camera capable of turning 360 degrees of the robot (eyes), the subway is respectively provided with the camera capable of turning 360 degrees, the obstacles in front, back, left and right are recognized, the radar sensor and the laser range finder analyze the traffic condition, and the navigation of the road ahead is carried out through a detailed map, which is realized through a computer data center, like the human brain, it is used to make judgment decision, after obtaining information from the road recognition device, it is necessary to make judgment, whether the subway is on or off, and whether the subway is back or down, it is necessary to select the next action most suitable for the environment according to the actual situation at that time, the analyst gives full analysis to each situation in advance, the best group of operation parameters is inputted into the computer memory, when the vehicle is driven, a computer is used for carrying out corresponding retrieval, and the left wheel sensor and the right wheel sensor are used for positioning the position of the subway; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the vehicle body to execute task operation; the robot automatically identifies the coded parking spaces and the multi-branch paths, and the robot automatically identifies the accelerating, decelerating, right-angle turning, driving and parking identifiers; the robot intelligently identifies obstacles; decomposing a decision-making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection and path planning, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the subway, the cognition comprises the division of traffic flow states (such as sparseness and denseness), the game states of traffic participants (such as rush out ramps), the peripheral prediction outputs the states and the tracks of peripheral vehicles (including bicycles, pedestrians, automobiles, trains and subways) in a future period of time, and the behavior selection outputs a certain type of driving behaviors (such as overtaking, lane changing, approaching, following, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, vehicle dynamics model, driving experience, rules).

4. A novel piloting system of an aircraft; is characterized in that: robots replace human piloted aircraft systems; comprises the following steps:

the system for replacing human piloting the airplane by the robot consists of a sensor, a signal conditioning circuit, a converter, a computer display, a data processing device, a road image recognition device, a transmission and power system, an initialization, an execution mechanism, an adapter, a man-machine interface, the robot, an alarm system, a piloting system, a nervous system thinking, a sensing network and a motion system; the robot replaces a human piloted airplane system structure and comprises a starting system, a received information, a check information, a retransmission, a check passing, a received information, a system requirement analysis, a system overall design, a sampling rate determination, a scale conversion design, a microprocessor chip selection, a movement detection, a vehicle identification, a human face identification, a hardware circuit design, a hardware circuit debugging, a software program design, a software program debugging, a software and hardware joint debugging, a monitoring operation, an environment sensing, a behavior prediction, a planning execution, an operating system, a high-precision positioning, a high-precision map, a system safety, a system overall performance test, a system integration and maintenance, a design scheme modification, an automatic piloting grading standard, an analysis processing, a state identification, a signal acquisition, a data display, a video storage, a fault code recording, a pace correction, a voice module, an infrared detection and a ground detection, the system comprises a driving circuit, a photoelectric conversion device, a touch module, a display module, a central processing unit, a mechanical structure system, a sensing system, a robot environment exchange system, a man-machine exchange system, an information processing system, a timing system, a vision module, GPS positioning, internet automatic driving, moving obstacle detection, moving obstacle collision track prediction, moving obstacle avoidance and shutdown system;

the robot system for replacing the human piloting airplane is characterized in that a robot road recognition device is arranged on a camera capable of turning 360 degrees of a robot (eyes), airplanes are respectively provided with the camera capable of turning 360 degrees, obstacles in front, back, left and right directions are recognized, a radar sensor and a laser range finder are used for analyzing traffic conditions, and the navigation of the road ahead is carried out through a detailed map, which is realized through a computer data center, like the human brain, is used for making judgment decision, after obtaining information from the road recognition device, the judgment is made, whether the airplane is started or stopped, and whether the airplane is backed or decelerated is selected according to the actual situation at the moment, an analyst gives full analysis to various situations in advance, the optimal group of operation parameters is input into a computer memory, during flying, a computer is used for carrying out corresponding retrieval, and the left and right wheel sensors are used for positioning the position of the airplane; the robot is divided into three modules, a perception module: acquiring and processing on-site environment information; a planning module: analyzing the task sequence to plan and make a decision; an execution module: driving the airplane to perform task operation; the robot automatically identifies the encoded parking positions and multi-branch paths, and the robot automatically identifies the signs of acceleration, deceleration, right-angle turning, flight, stop and flight; the robot intelligently identifies obstacles; decomposing a decision-making process into a series of independent sub-problems, such as situation cognition, peripheral prediction, behavior selection and path planning, wherein each problem is independently solved, the situation cognition outputs the cognition and the processing of the driving environment of the airplane, including the division of the flight state (such as sparseness and denseness), the game state (such as rush out of ramps) of traffic participants, the peripheral prediction outputs the state and the track of the peripheral airplane (including bicycles, pedestrians, automobiles, trains and subways) in a future period of time, and the behavior selection outputs a certain type of driving behavior (such as exceeding the airplane, changing lanes, approaching, following the airplane, free straight going and turning around); the layered decision scheme has the advantages that problems can be decomposed, tasks can be divided, and modularization is easy, so that a decision algorithm is high in computability and strong in interpretability, and engineering implementation is facilitated; it is a future development situation to fuse the layered framework and the learning method and to fuse the autonomous learning with the prior knowledge (road structure, flight dynamics model, driving experience, rules).