CN111813130A - Autonomous navigation obstacle avoidance system of intelligent patrol robot of power transmission and transformation station - Google Patents

Autonomous navigation obstacle avoidance system of intelligent patrol robot of power transmission and transformation station Download PDF

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Publication number
CN111813130A
CN111813130A CN202010834457.8A CN202010834457A CN111813130A CN 111813130 A CN111813130 A CN 111813130A CN 202010834457 A CN202010834457 A CN 202010834457A CN 111813130 A CN111813130 A CN 111813130A
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inspection robot
intelligent inspection
station
obstacle avoidance
data
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吴炜
颜文旭
许宇伟
黄鑫
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Jiangnan University
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Jiangnan University
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • G05D1/0248Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means in combination with a laser
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J19/00Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
    • B25J19/02Sensing devices
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J19/00Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
    • B25J19/02Sensing devices
    • B25J19/021Optical sensing devices
    • B25J19/022Optical sensing devices using lasers
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1656Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
    • B25J9/1666Avoiding collision or forbidden zones
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1679Programme controls characterised by the tasks executed
    • B25J9/1689Teleoperation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01DMEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00Measuring or testing not otherwise provided for
    • G01D21/02Measuring two or more variables by means not covered by a single other subclass
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0011Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0055Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements
    • G05D1/0061Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot with safety arrangements for transition from automatic pilot to manual pilot and vice versa

Abstract

The invention relates to the technical field of intelligent inspection robots, and particularly discloses an autonomous navigation obstacle avoidance system of an intelligent inspection robot for a power transmission and transformation station. The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station, provided by the invention, enables the inspection robot to timely and accurately respond to environmental changes to normally advance, further realizes reliable navigation, smoothly completes inspection tasks, has strong adaptability to complex site environments, and has the capability of autonomously handling emergency situations.

Description

Autonomous navigation obstacle avoidance system of intelligent patrol robot of power transmission and transformation station
Technical Field
The invention relates to the technical field of intelligent inspection robots, in particular to an autonomous navigation obstacle avoidance system of an intelligent inspection robot for a power transmission and transformation station.
Background
With the rapid development of computers and artificial intelligence technologies, all walks of life have intelligent express trains. Research on mobile robots relates to research results of a plurality of different subjects such as automatic control, machinery, computers, electronics, artificial intelligence and the like; the intelligent vehicle system is developed in a burst mode under the rapid development of electronic technology and the enhancement and improvement of an AI (Artificial Intelligence) algorithm theory, the basic principle is to utilize a sensor and a controller to acquire, process and execute information, but the more important core is the reasonable processing capacity of the intelligent algorithm on acquired data, and an intelligent mobile trolley can replace manpower in many fields and occasions, so that the cost is reduced, and the safety of workers is improved.
However, many current researches on intelligent driving vehicles are not perfect enough, and especially, the reliability of the intelligent driving vehicles is difficult to ensure when the intelligent driving vehicles are applied to special fields such as power transmission and transformation stations under the working conditions of complex operation environments, on the fields, power transmission and transformation circuits are complex, various electrical equipment are various, and various devices are difficult to accurately identify, and meanwhile, if the conditions such as personnel walking or temporarily placed safety fences are met in the inspection process, the inspection vehicles cannot timely and accurately cope with environmental changes and cannot normally travel, so that reliable navigation cannot be realized, and inspection tasks cannot be smoothly completed; these situations illustrate that the existing intelligent inspection robot has poor adaptability to complex field environments and insufficient capability of autonomously handling emergency situations.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides the autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station, so that the inspection robot can timely and accurately respond to environmental changes to normally advance, further realize reliable navigation and smoothly complete inspection tasks, has strong adaptability to complex field environments and has the capability of autonomously handling emergency situations.
As a first aspect of the invention, an autonomous navigation and obstacle avoidance system of an intelligent inspection robot for a power transmission and transformation station is provided, the autonomous navigation and obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station comprises an intelligent inspection robot and a user side, the intelligent inspection robot comprises a middle control station, and a laser radar, a binocular camera, a measuring instrument, a rotating pan-tilt mechanical arm and a mobile chassis driver which are respectively connected with the middle control station, the user side comprises a cloud server, an upper monitoring station and a standby remote controller, the middle control station is also respectively connected with the cloud server, the upper monitoring station and the standby remote controller,
the laser radar is used for scanning the surrounding environment to obtain laser point cloud data;
the binocular camera is used for shooting the surrounding environment to obtain depth image data;
the control console is used for analyzing the acquired laser point cloud data and depth image data, generating action control instructions and respectively sending the action control instructions to the moving chassis driver and the rotating holder manipulator;
the mobile chassis driver is used for realizing the autonomous motion of the intelligent inspection robot according to the motion control instruction and feeding back the real-time motion state of the intelligent inspection robot to the control center;
the rotating holder manipulator is used for realizing corresponding operation functions according to the action control instructions and feeding back a real-time operation state to the console;
the measuring instrument is used for detecting surrounding environment data and various operating data of target equipment in real time and feeding back the measured data to the console;
the upper monitoring station is used for receiving the measurement data sent by the console and the state information of the intelligent inspection robot, visually displaying the measurement data and the state information on a display and supporting a user to issue a task instruction in a visual display interface; the intelligent inspection robot self state information comprises a real-time motion state and an operation state of a rotating holder manipulator;
the cloud server is used for receiving the measurement data sent by the console in the control and the state information of the intelligent inspection robot; the intelligent inspection robot self state information comprises a real-time motion state and a real-time operation state of a rotating holder manipulator;
and the standby remote controller is used for remotely controlling the intelligent inspection robot in emergency.
Further, the measuring instrument comprises an infrared thermometer, a thermal imager and a temperature and humidity measuring instrument.
Further, the intelligent inspection robot further comprises a wheel type chassis, a frame of a profile structure is arranged on the wheel type chassis, the laser radar and the measuring instrument are installed at the top of the frame, the console is installed at the bottom of the frame, the rotating tripod head mechanical arm is installed at the front of the frame, and the binocular camera is installed on the rotating tripod head mechanical arm.
Further, the binocular camera adopts a 2k binocular camera of STEREOLABS, and the model is ZED 2.
Further, the laser radar adopts RS-LiDAR-16 laser radar.
The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station, provided by the invention, has the following advantages: the inspection robot can timely and accurately respond to environmental changes to normally advance, reliable navigation is further achieved, inspection tasks are smoothly completed, adaptability to complex field environments is high, and the inspection robot has the capability of autonomously handling emergency situations.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a schematic structural diagram of an autonomous navigation obstacle avoidance system of an intelligent inspection robot for a power transmission and transformation station according to an embodiment of the present invention.
Fig. 2 is a flowchart of real-time map construction using SLAM algorithm according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention for achieving the predetermined purpose, the following detailed description will be made on the specific implementation, structure, features and effects of the autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station according to the present invention with reference to the accompanying drawings and preferred embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
In this embodiment, an autonomous navigation and obstacle avoidance system of an intelligent inspection robot for a power transmission and transformation station is provided, fig. 1 is a schematic structural diagram of the autonomous navigation and obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station provided by the present invention, as shown in fig. 1, the autonomous navigation and obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station includes an intelligent inspection robot and a user side, the intelligent inspection robot includes a middle control station, and a laser radar, a binocular camera, a measuring instrument, a rotating pan-tilt manipulator and a mobile chassis driver which are respectively connected with the middle control station, the user side includes a cloud server, an upper monitoring station and a standby remote controller, the middle control station is also respectively connected with the cloud server, the upper monitoring station and the standby remote controller,
the laser radar is used for scanning the surrounding environment to obtain laser point cloud data;
the binocular camera is used for shooting the surrounding environment to obtain depth image data;
the control console is used for analyzing the acquired laser point cloud data and depth image data, generating action control instructions and respectively sending the action control instructions to the moving chassis driver and the rotating holder manipulator;
the mobile chassis driver is used for realizing the autonomous motion of the intelligent inspection robot according to the motion control instruction and feeding back the real-time motion state of the intelligent inspection robot to the control center;
the rotating holder manipulator is used for realizing corresponding operation functions according to the action control instructions and feeding back a real-time operation state to the console;
the measuring instrument is used for detecting surrounding environment data and various operating data of target equipment in real time and feeding back the measured data to the console;
the upper monitoring station is used for receiving the measurement data sent by the console and the state information of the intelligent inspection robot, visually displaying the measurement data and the state information on a display and supporting a user to issue a task instruction in a visual display interface; the intelligent inspection robot self state information comprises a real-time motion state and an operation state of a rotating holder manipulator;
the cloud server is used for receiving the measurement data sent by the console in the control and the state information of the intelligent inspection robot; the intelligent inspection robot self state information comprises a real-time motion state and a real-time operation state of a rotating holder manipulator;
and the standby remote controller is used for remotely controlling the intelligent inspection robot in emergency.
The wheel type chassis adopts a modularized and intelligent design concept on the whole, adopts a composite design of an inflatable rubber wheel and an independent suspension on a power module, and is additionally provided with a powerful direct-current brushless servo motor, so that the chassis development platform has strong trafficability and ground adaptability and can flexibly move on different grounds; safety anti-collision pipes are arranged around the wheeled mobile robot, so that the damage to a vehicle body can be reduced when an emergency accident happens; the front and the back of the wheeled mobile robot are both provided with lamplight, and the front side adopts a white light design and can be used for illumination; the tail part adopts a prominent red tail lamp which can be used as a warning lamp and an indicator lamp; the left side and the right side of the emergency stop switch are respectively provided with the emergency stop switch, and the redundant design is adopted, so that the emergency stop operation can be quickly carried out in case of emergency, the occurrence of safety accidents is avoided, and unnecessary loss is reduced or avoided; open electrical interfaces and communication interfaces are arranged at the tail part and the top part of the wheeled mobile robot, so that secondary development is facilitated for customers, aviation waterproof connectors are adopted for the electrical interfaces in design and selection, on one hand, expansion and use of the customers are utilized, and on the other hand, the robot platform can be used in some severe environments.
Preferably, the measuring instrument comprises an infrared thermometer, a thermal imager and a temperature and humidity measuring instrument; the data acquisition is carried out by adopting a multi-sensor mode which takes binocular vision as a main part and takes an infrared thermometer, a thermal imager, a temperature and humidity measuring instrument and the like as auxiliary parts, and the omnibearing dead-angle-free detection is provided for monitoring various operation data of the power transmission and transformation station; in addition, in the binocular point cloud data, characteristic points of the equipment, such as appearance characteristics, labels and the like, are combined with calibration data of the camera to perform visual positioning and ranging on the target equipment, and the distance and the position of the target equipment relative to the mobile platform executing mechanism are obtained through pose calculation so as to further operate the equipment. Meanwhile, the visual inspection can also realize the function of detecting the structural defects of the equipment.
Specifically, the infrared thermometer can realize the local temperature detection function of the designated equipment, the thermal imager can realize the detection of temperature field data of the whole equipment or each position of the site, and the temperature and humidity sensor can realize the real-time detection of the environment temperature and humidity of the site of the power transmission and transformation station; the invention can integrate the detection equipment needed by the power transmission and transformation station, such as an infrared thermometer, a thermal imager, a temperature and humidity measuring instrument and the like, and can perform some basic image information identification such as visual reading table, visual structure defect detection and the like through vision, can complete the detection of each device of different transformer substations, realize the synchronous analysis and diagnosis of the multidimensional state quantity, find the failure symptom of the device in advance, when abnormal emergency such as detection data exceeding a safety threshold value is found, the intelligent inspection robot can be used as a mobile fault diagnosis platform to replace manual work to find out equipment faults in time, so that the safety risk of personnel is reduced, and the intelligent autonomous inspection system is cooperatively linked with a comprehensive management system, a production management system, a fire-fighting system, a security system, a video system and an in-station monitoring system of the power transmission and transformation station, and provides an omnidirectional intelligent autonomous inspection solution for monitoring various operation data of the power transmission and transformation station.
Preferably, the device abnormal noise malfunction determination is detected using an integrated microphone.
Preferably, the robot is patrolled and examined to intelligence still includes wheeled chassis, the frame of section bar structure is equipped with on the wheeled chassis, install at the top of frame lidar and measuring instrument, the control center is installed in the frame bottom, rotatory cloud platform manipulator is installed at the frame front portion, install on the rotatory cloud platform manipulator binocular camera.
Preferably, the binocular camera adopts a 2k binocular camera of STEREOLABS, and the model is ZED 2;
the ZED 2 is internally provided with an IMU (inertial measurement unit) and a barometer, low-drift pose information can be output at 100Hz, and in addition, the ZED 2 has a wide angle of 120 degrees, so that the position tracking precision is enhanced, and a cloud platform is supported.
Preferably, the laser radar adopts an RS-LiDAR-16 laser radar, the laser radar adopts RS-LiDAR-16 which is already produced in mass by Shenzhen Shangsheng Juanchu technology Limited, and the laser radar mainly faces the fields of automatic driving automobile environment perception, robot environment perception, unmanned aerial vehicle surveying and mapping and the like; the RS-LiDAR-16 simultaneously emits high-frequency laser beams to continuously scan the external environment through 16 laser transmitters, provides three-dimensional space point cloud data and object reflectivity through a high-speed digital signal processing technology and a ranging algorithm, enables a machine to see the surrounding world, and provides powerful guarantee for positioning, navigation, obstacle avoidance and the like.
The binocular camera on the intelligent inspection robot is mainly used for overcoming the defect that a laser radar cannot recognize optical texture information like human eye vision, forming complementary redundancy with a laser SLAM, and enhancing the stability of a system and the readability of drawing construction; meanwhile, vision can be used for carrying out accurate positioning based on semantic information near a target area, and plays an important role in equipment feature identification and distance measurement; providing precise position information for the manipulator to complete a fine automation task; the binocular vision algorithm is used for carrying out visual positioning and distance measurement on target equipment by identifying characteristic points, such as appearance characteristics, labels and the like, of the equipment in the binocular point cloud data and further combining calibration data of a camera, and obtaining the distance and the position of the target equipment relative to an execution mechanism of a mobile platform through pose calculation so as to further operate the equipment; in order to solve the problem that the visual angle of the binocular camera is limited, the binocular camera is arranged on a mechanical arm or an additional mechanical arm structure to rotate in multiple degrees of freedom.
Preferably, the main body of the rotating tripod head is a turntable and a built-in stepping motor, and the rotating tripod head can rotate at a certain speed for any angle by receiving a control command from an embedded control console.
It should be noted that the specific degree of freedom and the execution end of the manipulator need to be configured according to task requirements, and the embedded control console already reserves the interface of this part.
Preferably, the embedded console is developed by Jetson AGXXavier of NVIDIA, whose GPU workstation level performance is sufficient to accomplish the following tasks: visual ranging, sensor fusion, positioning and mapping, obstacle detection and a route planning algorithm which is crucial to a new generation of robots; furthermore, Jetson AGX Xavier can provide higher levels of computational density, energy efficiency, and AI reasoning capability at the edge.
The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station in the embodiment of the invention realizes four functions of automatic mapping and positioning, path planning, obstacle avoidance navigation and data monitoring, and provides monitoring pictures and remote control functions for users; wherein, the monitoring picture is an information display picture of an upper monitoring station; when the manual driving mode is started, the standby remote controller can move, turn and the like to the robot by operating the manipulator by a user.
Specifically, processing of sensing data of the laser radar and the binocular camera, path planning, navigation, obstacle avoidance, control of a rotating pan-tilt manipulator, acquisition of measuring instrument data and the like are all performed on an embedded control console, and a control command is issued to a robot moving chassis driver in real time to enable the robot moving chassis driver to complete real-time obstacle avoidance navigation actions.
Specifically, as shown in fig. 1, the console sends a control frame to the lidar through the Ethercat interface, the lidar scans the surrounding environment to obtain laser point cloud data, and feeds back the laser point cloud data to the console through the Ethercat interface, meanwhile, the console sends the control frame to the binocular camera through the usb3.0 interface, the binocular camera takes a binocular photograph, and feeds back the binocular photograph to the console through the usb3.0 interface; the control center station can obtain the next actions of the robot chassis through mapping positioning, path planning and obstacle avoidance navigation algorithms after obtaining data of the laser radar and the binocular camera, and sends chassis control frames to a driver of the wheel type chassis of the robot through a bus so as to realize autonomous movement of the robot, and can feed back the real-time movement state of the robot through chassis state frames; the rotating tripod head mechanical arm can realize corresponding operation functions, and the specific mode is that the control console sends a control frame to the rotating tripod head mechanical arm through a serial port, the rotating tripod head mechanical arm performs corresponding movement, and the movement state is fed back to the control console in real time through a state frame; the measuring instrument can realize various data detection functions, and the specific mode is that the control center sends a control frame to the measuring instrument through the bus, and the measuring instrument performs corresponding measurement work and feeds back a measurement data frame to the control center; an upper monitoring station of a user side can receive data information from the intelligent inspection robot through a network, visually display the data information on a display of the monitoring station and support a user to issue a task instruction in a visual interface; data of the robot wheel type chassis measuring instrument, robot state and other information can be transmitted to a cloud server of a user side through the Internet; the standby remote controller at the user side can operate the robot chassis when the robot needs human intervention operation in an emergency situation; the distributed deployment enables the whole system to be integrated in function, but the whole system is independent in data processing, stability of the system is enhanced, and meanwhile the system is easy to expand.
Specifically, the functions of map building and positioning in the power transmission and transformation environment can be realized through a SLAM algorithm with a laser radar as a main part and a binocular vision sensor as an auxiliary part; secondly, combining a global map obtained by SLAM and a routing inspection target appointed by a user to realize an autonomous routing inspection path planning function of the robot; then, the method detects obstacles in the environment in real time through a SLAM algorithm with a laser radar as a main part and a binocular vision sensor as an auxiliary part, and assigns a safe traveling route for the robot by combining the path planning algorithm.
Specifically, the SLAM algorithm is optimized in a mode that the visual odometer is cooperated with the high-precision sensor, the mapping is subjected to auxiliary constraint through the position information fed back by the high-precision differential GPS, and misjudgment of the robot on the self pose change due to the repeated scene characteristics is avoided. Through the high-precision gyroscope module, the small attitude change of the robot is acquired in real time, the point cloud data errors obtained by the laser radar and the binocular vision are compensated, the phenomenon of image construction distortion caused by small vibration and ground fluctuation is solved, and a foundation is laid for the reliable operation of the product in the complex and severe book and substation environment.
Specifically, the method is built on the basis of an intelligent mobile platform, a software system is constructed by using a distributed system, so that a user can remotely monitor the behavior of the wheeled mobile robot in a control room, obtain a global map and a local map near the wheeled mobile robot, and synchronously display the track and the planned track of the wheeled mobile robot.
In the wheel-type mobile robot, the processing of sensing data, the control of obstacle avoidance behaviors, the path planning and the tracking function are all carried out on an embedded control console, and a control command is issued to a chassis of the wheel-type mobile robot in real time, so that the chassis of the wheel-type mobile robot completes real-time obstacle avoidance navigation, and the execution efficiency and the safety of routing inspection work are improved; meanwhile, the PC terminal controlled by the user can receive information from the wheeled mobile robot through the network, visualize the information on the display and support the user to issue a control command in a visualization interface.
The flow of real-time map construction using the SLAM algorithm according to the present invention will be described in detail with reference to fig. 2.
As shown in fig. 2, the method mainly includes the steps of data preprocessing, front-end odometer, closed-loop detection, floor detection, rear-end optimization and map building, and specifically includes the following steps:
(1) data preprocessing: the collected data of each sensor is subjected to operations such as noise removal, timestamp synchronization, distortion correction and the like, so that the usability of the data is ensured;
(2) front-end odometer: carrying out pose registration by using the point cloud obtained by the laser radar, estimating pose change between each frame, and serving as a speedometer; the closed-loop detection and the floor detection utilize the characteristics of repeated and relatively flat working environment, provide higher-dimensional information for the mobile platform and assist the rear end in optimizing;
(3) and (3) rear-end optimization: optimizing the pose estimated by the front-end odometer by adopting a nonlinear optimization algorithm so as to improve the global consistency of the map;
(4) establishing a graph: and splicing the processed point cloud data according to the optimized pose output by the rear-end optimizer to obtain a final global map.
The frame realizes a real-time map building function, and by using the built map, the intelligent inspection robot can also locate the position of the intelligent inspection robot in the global map according to the relative distance between the current frame and the environmental object, so that the location is realized.
The realization of automatic navigation obstacle avoidance in the intelligent inspection robot system mainly comprises a milemeter node, a laser radar node, a positioning node, a transformation relation release node, a command node, a map release node, a chassis control node and a most core logic processing node, and specifically comprises the following steps:
(1) and (3) milemeter nodes: receiving information from the odometer, resolving mileage data according to a protocol, performing corresponding data processing, and outputting more accurate odometer information to a distributed network for other nodes to use;
(2) laser radar node: the intelligent inspection robot uses an external sensor with a laser radar as a main part and binocular vision as an auxiliary part, and a laser radar node receives a data packet from laser radar hardware, analyzes and repacks the data packet into information in a laser scanning laser or point cloud format according to a protocol and issues the information to a distributed network for other nodes to use;
(3) positioning a node: comparing information issued by a laser radar node with a map so as to determine the relative position of the node in the map, wherein an AMCL (advanced metering and coding) packet can be used in the map, a particle swarm filter algorithm is mainly adopted in the AMCL packet, the algorithm has better positioning accuracy in a small-scale area, but the occupied resources can be rapidly increased along with the increase of the scale of the map, the performance of a computer is influenced, and after the positioning is finished, the node can issue position information to a distributed network in real time for other nodes to use;
(4) transforming the relationship node: the wheeled mobile robot is provided with a plurality of sensors, the information of the sensors is established in a self coordinate system, and a map and an odometer also have the self coordinate system, so when the information is processed, the conversion relation among the coordinate systems is determined to accurately guide the action of the wheeled mobile robot; in the system, the code function of the part is extracted, an independent transformation relation publishing node is constructed, the transformation relation tree is maintained by the independent transformation relation publishing node, and the transformation relation tree is published to a distributed network for other nodes to use;
(5) the command node: in practical application, a user needs to go to a certain specified position on a map by a trolley to execute an inspection task, and a command node is constructed to convey a navigation target instruction of the user so as to meet the requirement that the user needs the wheeled mobile robot to go to the certain specified position on the map to execute the inspection task, so that a destination and the direction after the destination can be specified on the map, and information is automatically issued to a distributed network for other nodes to call;
(6) the map publishing node: in order to enable a user to normally navigate and enable the wheeled mobile robot to find a proper path, a global static map is indispensable, the map can be built in real time by using an SLAM algorithm, and an offline global point cloud map obtained by running the SLAM in the prior art can also be used; in the inspection task of the power transmission and transformation station, a static scene is basically unchanged and belongs to a structured scene, so that the off-line map is more convenient to directly use; it should be noted that in the navigation link, the user really needs a 2D overhead view rather than a 3D point cloud map, so some processing needs to be performed in a map publishing node, and the map is converted into a grid map and then published to a distributed network for other nodes to call;
(7) chassis control node: and receiving information issued by the odometer node, the laser radar node, the positioning node, the transformation relation issuing node, the command node and the map issuing node through the logic processing node, performing a series of logic processing and decision planning steps, calculating the proper chassis speed and direction of the wheeled mobile robot, issuing control information to a distributed network, and receiving the control information by the chassis control node, thereby completing the implementation of global path planning, local path planning and recovery behaviors.
The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station, provided by the invention, adopts a multifunctional modularized industry application mobile platform with a modularized and intelligent design concept, and has strong load capacity and a strong power system; the system is provided with equipment such as a binocular camera, a laser radar, a GPS module, an IMUS inertial sensor, an infrared thermometer, a thermal imager, a temperature And humidity measuring instrument, a manipulator And the like, integrates a SLAM (simultaneous Localization And mapping) synchronous positioning And mapping algorithm, a path planning algorithm And a path navigation algorithm, And simultaneously opens a visual interface for a user for remote monitoring And remote control; the intelligent mobile platform can be applied to the fields of unmanned inspection, security protection, scientific research, exploration, logistics and the like of the power transmission and transformation station; the intelligent inspection robot can be used as a movable monitoring platform, replaces manual work to find out equipment faults in time, reduces safety risks of personnel, is cooperatively linked with a comprehensive management system, a production management system, a fire protection system, a security system, a video system and a monitoring system in a station, and provides an all-round intelligent autonomous inspection solution for monitoring various operation data of a power transmission and transformation station.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (5)

1. The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the power transmission and transformation station is characterized by comprising an intelligent inspection robot and a user side, wherein the intelligent inspection robot comprises a middle control station, and a laser radar, a binocular camera, a measuring instrument, a rotary pan-tilt manipulator and a mobile chassis driver which are respectively connected with the middle control station, the user side comprises a cloud server, an upper monitoring station and a standby remote controller, the middle control station is also respectively connected with the cloud server, the upper monitoring station and the standby remote controller,
the laser radar is used for scanning the surrounding environment to obtain laser point cloud data;
the binocular camera is used for shooting the surrounding environment to obtain depth image data;
the control console is used for analyzing the acquired laser point cloud data and depth image data, generating action control instructions and respectively sending the action control instructions to the moving chassis driver and the rotating holder manipulator;
the mobile chassis driver is used for realizing the autonomous motion of the intelligent inspection robot according to the motion control instruction and feeding back the real-time motion state of the intelligent inspection robot to the control center;
the rotating holder manipulator is used for realizing corresponding operation functions according to the action control instructions and feeding back a real-time operation state to the console;
the measuring instrument is used for detecting surrounding environment data and various operating data of target equipment in real time and feeding back the measured data to the console;
the upper monitoring station is used for receiving the measurement data sent by the console and the state information of the intelligent inspection robot, visually displaying the measurement data and the state information on a display and supporting a user to issue a task instruction in a visual display interface; the intelligent inspection robot self state information comprises a real-time motion state and an operation state of a rotating holder manipulator;
the cloud server is used for receiving the measurement data sent by the console in the control and the state information of the intelligent inspection robot; the intelligent inspection robot self state information comprises a real-time motion state and a real-time operation state of a rotating holder manipulator;
and the standby remote controller is used for remotely controlling the intelligent inspection robot in emergency.
2. The autonomous navigation obstacle avoidance system of the intelligent inspection robot of the electric transmission and transformation station as claimed in claim 1, wherein the measuring instruments include an infrared thermometer, a thermal imager and a temperature and humidity measuring instrument.
3. The autonomous navigation obstacle avoidance system of the intelligent inspection robot for the electric transmission and transformation station as claimed in claim 1, wherein the intelligent inspection robot further comprises a wheel type chassis, a frame with a profile structure is mounted on the wheel type chassis, the laser radar and the measuring instrument are mounted at the top of the frame, the console is mounted at the bottom of the frame, the rotating tripod head manipulator is mounted at the front of the frame, and the binocular camera is mounted on the rotating tripod head manipulator.
4. The autonomous navigation obstacle avoidance system of the power transmission and transformation station intelligent inspection robot of claim 1, wherein the binocular camera is a 2k binocular camera of STEREOLABS, model number ZED 2.
5. The intelligent inspection robot autonomous navigation obstacle avoidance system according to claim 1, wherein the LiDAR employs an RS-LiDAR-16 LiDAR.
CN202010834457.8A 2020-08-19 2020-08-19 Autonomous navigation obstacle avoidance system of intelligent patrol robot of power transmission and transformation station Pending CN111813130A (en)

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CN112433535A (en) * 2020-11-18 2021-03-02 北京理工大学 Wheel-step composite mobile platform and multi-joint cooperative self-stabilizing method under obstacle crossing mode
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CN112433535A (en) * 2020-11-18 2021-03-02 北京理工大学 Wheel-step composite mobile platform and multi-joint cooperative self-stabilizing method under obstacle crossing mode
CN112433535B (en) * 2020-11-18 2022-03-25 北京理工大学 Wheel-step composite mobile platform and multi-joint cooperative self-stabilizing method under obstacle crossing mode
CN113799150A (en) * 2021-09-24 2021-12-17 南京信息工程大学 Gas concentration inspection robot based on indoor navigation and positioning and control method thereof
CN113650038A (en) * 2021-09-30 2021-11-16 中国华能集团清洁能源技术研究院有限公司 Inspection robot
CN114290313A (en) * 2021-12-17 2022-04-08 北京千替智能科技有限公司 Inspection robot, automatic navigation inspection robot system and control method
CN114290313B (en) * 2021-12-17 2024-02-02 北京千替智能科技有限公司 Inspection robot, automatic navigation inspection robot system and control method
CN114415699A (en) * 2022-04-02 2022-04-29 深圳市海纳鑫信息科技有限公司 Robot intelligent obstacle avoidance system capable of processing according to road surface information
CN115294411A (en) * 2022-10-08 2022-11-04 国网浙江省电力有限公司 Power grid power transmission and transformation image data processing method based on neural network
CN115294411B (en) * 2022-10-08 2022-12-30 国网浙江省电力有限公司 Power grid power transmission and transformation image data processing method based on neural network
CN115657645A (en) * 2022-11-16 2023-01-31 北京理工大学 Intelligent vehicle chassis and task load integrated control method and system
CN115657645B (en) * 2022-11-16 2023-04-11 北京理工大学 Intelligent vehicle chassis and task load integrated control method and system
CN115635486A (en) * 2022-12-23 2023-01-24 国网浙江宁波市鄞州区供电有限公司 Automatic monitoring, overhauling and disaster-resisting robot system of underground unmanned power station

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