CN108858195A - A kind of Triple distribution control system of biped robot - Google Patents

A kind of Triple distribution control system of biped robot Download PDF

Info

Publication number
CN108858195A
CN108858195A CN201810775243.0A CN201810775243A CN108858195A CN 108858195 A CN108858195 A CN 108858195A CN 201810775243 A CN201810775243 A CN 201810775243A CN 108858195 A CN108858195 A CN 108858195A
Authority
CN
China
Prior art keywords
layer
motion planning
robot
decision making
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810775243.0A
Other languages
Chinese (zh)
Inventor
董芹鹏
郑随兵
张颖
张旭龙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Rulman Intelligent Technology (beijing) Co Ltd
Original Assignee
Rulman Intelligent Technology (beijing) Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Rulman Intelligent Technology (beijing) Co Ltd filed Critical Rulman Intelligent Technology (beijing) Co Ltd
Priority to CN201810775243.0A priority Critical patent/CN108858195A/en
Publication of CN108858195A publication Critical patent/CN108858195A/en
Pending legal-status Critical Current

Links

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1602Programme controls characterised by the control system, structure, architecture

Landscapes

  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Manipulator (AREA)

Abstract

The invention discloses the Triple distribution control systems of biped robot a kind of, belong to technical field of robot control.Present system includes interactive decision making layer, motion planning layer and hardware driving layer;Interactive decision making layer is used for human-computer interaction, control instruction is sent to motion planning layer, motion planning layer receives and parses through the control instruction of interactive decision making layer transmission and is handed down to hardware driving layer, hardware driving layer receives the control instruction of motion planning layer, while acquisition hardware data and being uploaded to motion planning layer.Triple distribution control system is separately operable on two computers and driving chip, and three layers cooperate, and is not depended on mutually.Three-tier system of the invention independently realizes that the degree of coupling is low, and it is convenient to develop, and can acquire ambient data in real time and control robot and make corresponding actions, does not need largely program to prepare, substantially increases system effectiveness to a certain extent.

Description

A kind of Triple distribution control system of biped robot
Technical field
The present invention relates to three layers of distributions of robot and its control system technical field more particularly to a kind of biped robot Formula control system.
Background technique
In the control system of existing robot, integrated system is generallyd use, control function is all highly concentrated in one Perhaps function and processing task all on host is all focused on by server or host server.But it is actually answering In, integrated system is not able to satisfy the robot control field with huger functional requirement, and client needs at distribution Reason ability, complete integrated distributed system.
Distributed system is the set of several computers, and inside is realized by communication network, to communicate as network foundation.Entirely For distributed system using autonomous working or cooperation work two ways, each operation host can be with parallel work-flow and distribution control System.
Distributed system has certain superiority compared with traditional communication network:
1) each operation host parallel operation in distributed system, it is meant that realize the independence in physical property with And the cooperative on logic property;
2) distributed system reliability with higher, when one in system or multiple host break down, remaining Independent host can with self-healing, reconstitute with the consistent system of original system function, adjust entire distributed system automatically Section is restored to pre-fault status.
In recent years, biped robot has been widely used, and traditional technical method uses operator's off-line programing The mode of guidance controls robot, and the program being stored in internal storage location is repeatedly carried out in robot, completes required operation Movement, this control mode is restricted to robot extremely strong, does not have real-time, not to the sensing capability of extraneous information change Foot, can not be adjusted correspondingly operation behavior according to the variation of environment, while a large amount of function needs a large amount of programming Time greatly reduces system effectiveness to a certain extent.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of robot Triple distribution control system, surrounding can be acquired in real time It environmental data and controls robot and makes corresponding actions, improve system effect.
The Triple distribution control system of biped robot provided by the invention a kind of, including interactive decision making layer, movement rule Draw layer and hardware driving layer.The interactive decision making layer is used for multi-modal human-computer interaction, sends control instruction to the motion planning Layer, and receive the data that the motion planning layer is sent;The motion planning layer is for receiving and parsing through the interactive decision making layer The control instruction of transmission is simultaneously handed down to the hardware driving layer, while the friendship is sent to after the information of receiving sensor and processing Mutual decision-making level;The hardware driving layer is used to receive the control instruction of the motion planning layer, at the same acquisition hardware data and on It is transmitted to the motion planning layer.
The hardware driving layer includes motor driven and data acquisition, and the hardware driving layer executes following steps:
S11 receives the position data of the motion planning layer, given according to PID (proportional-integral-differential) control algolithm Motor speed, turnning circle and acceleration;
S12, encoder position, temperature, voltage and the error message of acquisition hardware, feedback data give the hardware driving Layer.
Further, the motion planning layer, external laser radar obtain point cloud data;External attitude transducer, is obtained Take robot centroid position posture;The six-dimension force sensor in two leg vola of robot is connected, robot foot bottom stress and power are obtained Square;Interactive decision making layer control instruction is received by Ethernet interface;Instruction is sent to hardware driving layer by CAN bus and receives number According to.The function that the motion planning layer is realized includes that positive inverse kinetics solution is calculated, dynamics resolves, instruction parses and navigation programming. The motion planning layer executes following steps:
S21, after starting up, the motion planning layer enters Auto-Sensing Mode, detection CAN device, joint of robot ID and Joint of robot original state is inquired, if mistake occurs, corresponding error code is sent to the interactive decision making layer.
S22 receives the instruction that the motion planning layer is sent, and analyzes the instruction;
S23, if interactive decision making layer transmission is navigation instruction, information carries out the motion planning layer according to the map The navigation programming makes robot reasonable avoidance on the walking path;
S24 carries out positive inverse kinetics solution calculation according to the robot ambulation path, calculates each joint of biped robot Position in the process of walking;
S25, the data of the robot pose and vola power and torque that are obtained according to the sensor, carries out the dynamics It resolves, maintains the dynamic stability of robot in the process of walking.
The position in each joint of the robot of calculating is sent to the hardware driving layer, and obtains the hardware driving by S26 The data of layer feedback.
S27 is sent to institute after being packaged the point cloud data of the data of hardware driving layer feedback and the laser radar State interactive decision making layer.
Further, the interactive decision making layer, External microphone array carry out voice pickup and interact with speech synthesis; External depth camera obtains color image and depth point cloud data;By Ethernet interface to motion planning layer send instruction and Receive data.The function that the interactive decision making layer is realized include interactive voice, visual interactive, three-dimensional artificial, interface alternation and Build figure navigation.The interactive decision making layer executes following steps:
S31 after computer starting, receives the data that the motion planning layer uploads, detecting each equipment has fault-free first;
S32 is carried out interactive voice, identifies the sound of people around, interacted with English and Chinese bilingual;In voice In interactive process, key vocabularies are picked up, triggering is stored in the task sequence of interactive decision making layer, completes specified operation.
S33 carries out visual interactive, obtains face information using the RGB image of depth camera, carries out recognition of face and people Face dynamically track.
S34 carries out three-dimensional artificial, using RVIZ the and GAZEBO emulation platform of ROS operating system, is advised according to the movement Draw the real time kinematics posture for the joint angles dummy robot that layer is fed back to;
S35 carries out interface alternation, realizes to be integrated in the developing plug of RVIZ, the information in showing interface joint, user It can control the movement of simple joint at interface or control robot and walk according to scheduled route;
S36 is carried out building figure navigation, is established three-dimensional artificial map in RVIZ using the point cloud data of depth camera, use It is a little target point that family, which is arbitrarily picked up in map with mouse, and interactive decision making layer is handed down to the progress of motion planning layer after generating path Navigation programming.
Advantages of the present invention is with good effect:
(1) the Triple distribution control system of biped robot of the invention, be divided into interactive decision making layer, motion planning layer and Hardware driving layer, each layer ability independently realize that the degree of coupling is low, and it is convenient to develop, and improve the reliability and stability of system.
(2) the Triple distribution control system of biped robot of the invention can acquire in real time ambient data simultaneously And control robot makes corresponding actions, does not need largely program to prepare, substantially increases system to a certain extent Efficiency.
Detailed description of the invention
Fig. 1 is the functional schematic of the Triple distribution control system of the biped robot of the embodiment of the present invention;
Fig. 2 is the structural schematic diagram of the Triple distribution control system of the biped robot of the embodiment of the present invention;
Fig. 3 is that the assignment decisions layer of the Triple distribution control system of the biped robot of the embodiment of the present invention executes process Figure;
Fig. 4 is that the motion planning layer of the Triple distribution control system of the biped robot of the embodiment of the present invention executes process Figure;
Fig. 5 is that the hardware driving layer of the Triple distribution control system of the biped robot of the embodiment of the present invention executes process Figure.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that Specific embodiment described herein is only used for explaining related content, rather than limitation of the invention.Further need exist for explanation It is that for ease of description, only the parts related to the present invention are shown in attached drawing.
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the present invention can phase Mutually combination.Below with reference to the accompanying drawings 1-4 and in conjunction with the embodiments come the present invention will be described in detail.
As shown in Figure 1, the Triple distribution control system of biped robot, including interactive decision making layer, motion planning layer and Hardware driving layer.Wherein, interactive decision making layer realize function include interactive voice, visual interactive, three-dimensional artificial, interface alternation and Build figure navigation;The function that motion planning layer is realized includes that positive inverse kinetics solution is calculated, dynamics resolves, sensing data obtains, refers to Enable parsing and navigation programming;The function that hardware driving layer is realized includes motor driven and data acquisition.Interactive decision making layer is for more Mode human-computer interaction sends control instruction to motion planning layer, and receives the data of motion planning layer transmission.Motion planning layer is used In the control instruction for receiving and parsing through the transmission of interactive decision making layer and it is handed down to hardware driving layer, receives the number of hardware driving layer feedback According to, while interactive decision making layer is sent to after the information of receiving sensor and processing.Hardware driving layer is for receiving motion planning layer Control instruction, while acquisition hardware data and being uploaded to motion planning layer.
As shown in Fig. 2, the Triple distribution control system of biped robot is separately operable in two computers and driving core On piece, three layers cooperate, and do not depend on mutually.The computer of interactive decision making layer and the computer of motion planning layer are mounted on robot In the control cabinet at top, communicated between each other by Ethernet interface.It is driven by 12 joints the leg of biped robot Dynamic movement solidifies the embedded system for realizing hardware driving layer function, 12 all passes in the driving chip in each joint Drive system in section forms hardware planning layer, unified to be communicated by CAN bus and the computer of motion planning layer.
Interactive decision making layer is carried out voice pickup and is interacted with speech synthesis by the port RS232 External microphone array;Pass through The external depth camera of USB interface obtains color image and depth point cloud data;It is sent by Ethernet interface to motion planning layer Instruction receives data.In interactive decision making layer, the interactive voice uses voice interaction module, can be carried out Chinese and English dialogue;It is described Visual interactive realizes that the color image that the depth camera obtains is used for recognition of face, the depth using depth camera The depth point cloud data that camera obtains is established for three-dimensional map and the figure of building navigates;The three-dimensional artificial obtains movement rule Draw the robot joint angles that layer uploads and the in the three-dimensional model posture of real-time display robot;The interface alternation is integrated in In the three-dimensional artificial, for controlling robot single joint movement, change joint of robot ID and setting dead-center position, and in real time Show joint angles, voltage, temperature, error code and the enabled bit flag of robot.
Motion planning layer obtains point cloud data, for keeping away during navigation programming by the external laser radar of USB port Barrier;By the external attitude transducer of USB port, robot centroid position posture is obtained;Machine is connected by two ports RS232 The six-dimension force sensor in two leg vola of people obtains robot foot bottom stress and torque;Interactive decision making layer is received by Ethernet interface Control instruction;It is sent and is instructed to hardware driving layer by CAN bus, receive data.The robot mass center that motion planning layer obtains The data of position and attitude and vola power and torque resolve for dynamics, keep the dynamic stability and stationarity of robot.
The operation for embedded system of hardware driving layer carries out motor on driving chip, through PWM (pulse width modulation) Driving controls joint motions;Encoder data is obtained by SPI (Serial Peripheral Interface (SPI)), calculates the position in joint;Pass through ADC (analog-digital converter) obtains the temperature and information of voltage of sensor, and the numerical value of joint overheat protector is arranged;Pass through CAN (control Device local area network processed) bus receives the control instruction of motion planning layer, and feedback data.
As shown in figure 3, the robot information that motion planning layer uploads is obtained first after user starts interactive decision making layer, Comprising data such as each joint position, voltage, enable bit, temperature and error codes, system is initialized, and is opened after initializing successfully Each subsystem that begins is run.
Interactive voice is completed by voice module, is analyzed using the sound source that microphone picks up surrounding, passes through semantic analysis Synthesis voice finishes playing interaction afterwards, and specific key vocabularies are in addition stored in voice module, after picking up to these vocabulary, Corresponding task sequence can be triggered, which is handed down to motion planning layer and completes particular task.
Interface alternation is that the plug-in unit based on RVIZ is developed, the angle position in each joint of real-time display robot, electricity Pressure, enable bit, temperature and error code, while user can also control simple joint in interface, such as ID modification, enable Position, setting zero-bit and target position, after user triggers these operations, system generates corresponding control instruction according to communications protocol Frame.
RGB image of the visual interactive based on depth camera, after obtaining color image, automatic program identification face letter Breath marks out face title, dynamic tracing display face letter when face information is with information matches in the database are stored Breath;If can not match, user's more new database is prompted.
Point cloud data of the figure navigation based on depth camera is built, three-dimensional map is generated in RVIZ, when user is in map After picking up a target point with mouse, system according to the map in situation, automatic avoiding barrier cooks up reasonable walking road Diameter, and motion planning layer is handed down in the path.
Three-dimensional artificial is completed based on RVIZ three-dimensional platform, and system obtains the joint angles that motion planning layer uploads, analog machine The posture of device people's threedimensional model.Meanwhile GAZEBO and RVIZ shared data interface is, it can be achieved that associative simulation, user can be intuitively See the real-time attitude of robot.GAZEBO is a kind of robot simulation software, is substantially carried out the emulation of robot dynamics.
As shown in figure 4, motion planning layer starting after, system is initialized first, detect joint ID sequence document and Corresponding error code is then sent to interactive decision making in case of mistake by CAN device, inquiry joint of robot original state Layer prompts user to break down.
Firstly, setting 500ms timing, motion planning layer send inquiry instruction frame and give hardware driving layer, inquire each joint and work as Preceding angle, temperature, voltage, enable bit and error code.
The instruction that interactive decision making layer is sent is divided into two kinds after parsing, first is that the simple joint control that interface alternation is sent refers to It enables, comprising position control, zero position, ID modification and the enable bit modification to particular joint, generates and instruct according to communications protocol Frame is sent to hardware driving layer;Second is that the task sequence and guidance path that send, motion planning layer carries out navigation programming.In interaction Under the elementary path that decision-making level generates, according to the data information that laser radar returns, determination occurs interim on current path Barrier, system carry out contexture by self and hide, after clearing the jumps, return to initial path and continue on.Interactive decision making layer is right The data of hardware driving layer feedback are parsed, and the current location returned according to joint and traveling posture carry out positive inverse kinematics It resolves, calculates the position in each joint of subsequent time robot.Meanwhile being passed back according to six-dimension force sensor and attitude transducer Power, torque and posture information carry out dynamics resolving, to the target position in joint on the basis of guaranteeing that Robotic Dynamic is stablized It is adjusted, then generates command frame and be handed down to hardware driving layer.The data that interactive decision making layer also feeds back hardware driving layer into It transmits with the point cloud data of laser radar after row parsing and gives interactive decision making layer.
As shown in figure 5, system is initialized, and detecting each joint driver, whether there is or not excess temperature guarantors after the starting of hardware driving layer Error code is sent to motion planning layer if generating system mistake by shield, position limitation protection and overcurrent protection.
The control instruction that motion planning layer is sent to hardware driving layer is divided into two kinds, first is that inquiry instruction, inquires robot Position, voltage, temperature, enable bit and the error code in each joint, hardware driving layer carry out data after receiving inquiry instruction Then acquisition generates status frames and is sent to motion planning layer;Second is that control instruction, after hardware driving layer receives control instruction, According to target position and current location, revolving speed, turnning circle and the acceleration of motor are calculated by pid control algorithm, are realized Motor driven, makes that robot is steady, moves rapidly to designated position.
It will be understood by those of skill in the art that above embodiment is used for the purpose of clearly demonstrating the present invention, and simultaneously Non- be defined to the scope of the present invention.For those skilled in the art, may be used also on the basis of disclosed above To make other variations or modification, and these variations or modification are still in range disclosed by the invention.

Claims (8)

1. the Triple distribution control system of biped robot a kind of, which is characterized in that including interactive decision making layer, motion planning layer With hardware driving layer;
The interactive decision making layer is used for multi-modal human-computer interaction, sends control instruction to the motion planning layer, and described in reception The data that motion planning layer is sent;
The motion planning layer is used to receive and parse through the control instruction that the interactive decision making layer is sent and is handed down to the hardware Layer is driven, the data of the hardware driving layer feedback are received, while being sent to the friendship after the information of receiving sensor and processing Mutual decision-making level;
The hardware driving layer is used to receive the control instruction of the motion planning layer, while acquisition hardware data and being uploaded to institute State motion planning layer;
The hardware driving layer includes motor driven and data acquisition, and the hardware driving layer executes following steps:
S11 receives the position data of the motion planning layer, gives motor speed, turnning circle according to pid control algorithm and adds Speed;PID indicates proportional-integral-differential;
S12, encoder position, temperature, voltage and the error message of acquisition hardware, feedback data give the motion planning layer.
2. dcs according to claim 1, which is characterized in that the interactive decision making layer, motion planning Layer is respectively arranged on one computer, and computer is mounted in the control cabinet at the top of robot, and computer passes through between each other Ethernet interface is communicated;The hardware planning layer by biped robot leg all intra-articular drive system groups At being communicated by CAN bus and the computer of motion planning layer;CAN indicates controller local area network.
3. dcs according to claim 1, which is characterized in that the motion planning layer, external laser Radar obtains point cloud data;External attitude transducer obtains robot centroid position posture;Connect two leg vola of robot Six-dimension force sensor obtains robot foot bottom stress and torque;Interactive decision making layer control instruction is received by Ethernet interface;Pass through CAN bus sends instruction to hardware driving layer and receives data;CAN indicates controller local area network.
4. dcs according to claim 1 or 3, which is characterized in that the motion planning layer was realized Function includes that positive inverse kinetics solution is calculated, dynamics resolves, instruction parses and navigation programming;The motion planning layer executes following step Suddenly:
S21, after starting up, motion planning layer enters Auto-Sensing Mode, detection CAN device, joint of robot ID and inquiry machine Corresponding error code is sent to the interactive decision making layer if mistake occurs by person joint's original state;ID indicates identification Number;
S22 receives the instruction that the motion planning layer is sent, and analyzes the instruction;
S23, if interactive decision making layer transmission is navigation instruction, the motion planning layer according to the map navigate by information Planning, makes robot avoidance on the walking path;
S24 carries out positive inverse kinetics solution calculation according to robot ambulation path, calculates each joint of biped robot in walking process In position;
S25, the robot pose and vola power and torque obtained according to attitude transducer and six-dimension force sensor, carries out dynamics It resolves;
The position in each joint of calculating is sent to hardware driving layer by S26, and obtains the data of hardware driving layer feedback;
S27 is sent to interactive decision making layer after being packaged the point cloud data of data and laser radar that hardware driving layer is fed back.
5. dcs according to claim 1, which is characterized in that the interactive decision making layer, external Mike Wind array carries out voice pickup and interacts with speech synthesis;External depth camera obtains color image and depth point cloud data; Instruction is sent to motion planning layer by Ethernet interface and receives data.
6. dcs according to claim 1 or 5, which is characterized in that the interactive decision making layer was realized Function includes interactive voice, visual interactive, three-dimensional artificial, interface alternation and builds figure navigation;The interactive voice is handed over using voice Mutual module carries out Chinese and English dialogue;The visual interactive uses depth camera, the color image that the depth camera obtains For recognition of face, the depth point cloud data that the depth camera obtains is established for three-dimensional map and the figure of building navigates; The robot joint angles of the three-dimensional artificial acquisition motion planning layer upload and in the three-dimensional model real-time display robot Posture;The interface alternation is integrated in the three-dimensional artificial, for controlling robot single joint movement, change joint of robot ID and setting dead-center position, and the joint angles of real-time display robot, voltage, temperature, error code and enabled bit flag.
7. dcs according to claim 1 or 5, which is characterized in that the interactive decision making layer executed Step includes:
S31, after computer starting, the data that uploads of reception motion planning layer first, detecting each equipment has fault-free;
S32 is carried out interactive voice, identifies the sound of people around, interacted with English and Chinese bilingual;In interactive process In, key vocabularies are picked up, triggering is stored in the task sequence of interactive decision making layer, completes specified operation;
S33 carries out visual interactive, obtains face information using the color image of depth camera, carries out recognition of face and face Dynamically track;
S34 carries out three-dimensional artificial, using RVIZ the and GAZEBO emulation platform of ROS operating system, is fed back according to motion planning layer The real time kinematics posture of the joint angles dummy robot returned;
S35 carries out interface alternation, and the plug-in unit by being integrated in RVIZ realizes that the information in showing interface joint, user is at interface The movement or control robot for controlling simple joint are walked according to scheduled route;
S36 carries out building figure navigation, establishes three-dimensional artificial map, Yong Hu in RVIZ using the point cloud data of depth camera Being picked up in map with mouse is a little target point, is handed down to motion planning layer behind interactive decision making layer generation path and carries out navigation rule It draws.
8. the dcs according to claim 1 or 2, which is characterized in that the hardware driving layer Operation for embedded system on driving chip, pass through PWM carry out motor driven, control joint motions;It is obtained and is encoded by SPI Device data calculate the position in joint;The temperature and voltage of sensor are obtained by ADC, and the number of joint overheat protector is set Value;The control instruction of motion planning layer, and feedback data are received by CAN bus;Wherein, PWM is pulse width modulation, SPI For Serial Peripheral Interface (SPI), ADC is analog-digital converter.
CN201810775243.0A 2018-07-16 2018-07-16 A kind of Triple distribution control system of biped robot Pending CN108858195A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810775243.0A CN108858195A (en) 2018-07-16 2018-07-16 A kind of Triple distribution control system of biped robot

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810775243.0A CN108858195A (en) 2018-07-16 2018-07-16 A kind of Triple distribution control system of biped robot

Publications (1)

Publication Number Publication Date
CN108858195A true CN108858195A (en) 2018-11-23

Family

ID=64302031

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810775243.0A Pending CN108858195A (en) 2018-07-16 2018-07-16 A kind of Triple distribution control system of biped robot

Country Status (1)

Country Link
CN (1) CN108858195A (en)

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110587601A (en) * 2019-08-20 2019-12-20 广西诚新慧创科技有限公司 Control system applied to intelligent inspection robot
CN111161424A (en) * 2019-12-30 2020-05-15 浙江欣奕华智能科技有限公司 Three-dimensional map determination method and determination device
CN111414688A (en) * 2020-03-18 2020-07-14 上海机器人产业技术研究院有限公司 Mobile robot simulation system and method based on UNITY engine
CN112025704A (en) * 2020-08-25 2020-12-04 杭州湖西云百生科技有限公司 Real-time distributed robot control method and system based on memory type database
CN113183162A (en) * 2021-04-28 2021-07-30 哈尔滨理工大学 Intelligent nursing robot control method and system
CN113485325A (en) * 2021-06-16 2021-10-08 重庆工程职业技术学院 SLAM mapping and autonomous navigation method for underground coal mine water pump house inspection robot
CN113524166A (en) * 2021-01-08 2021-10-22 腾讯科技(深圳)有限公司 Robot control method and device based on artificial intelligence and electronic equipment
CN114102582A (en) * 2021-11-11 2022-03-01 上海交通大学 Electrical system for super-redundant robot and working method thereof
CN114147721A (en) * 2021-12-15 2022-03-08 东北大学 Robot control system and method based on EtherCAT bus
CN114393563A (en) * 2021-12-21 2022-04-26 昆山市工研院智能制造技术有限公司 Real platform of instructing of operation robot is removed in indoor branch of academic or vocational study
CN114415653A (en) * 2021-12-01 2022-04-29 中国船舶重工集团公司第七一九研究所 Hybrid control system suitable for unmanned aerial vehicle under water
CN114505853A (en) * 2021-12-30 2022-05-17 爱普(福建)科技有限公司 Remote layered management and control method and system for industrial robot
CN114603540A (en) * 2020-12-09 2022-06-10 国核电站运行服务技术有限公司 Nuclear reactor pressure vessel detection manipulator control system
CN114932961A (en) * 2022-06-15 2022-08-23 中电海康集团有限公司 Four-footed robot motion control system
CN115026820A (en) * 2022-06-09 2022-09-09 天津大学 Control system and control method for man-machine cooperation assembly robot
WO2023124326A1 (en) * 2021-12-28 2023-07-06 上海神泰医疗科技有限公司 Robot control method, control device, robot system, and readable storage medium
CN116713992A (en) * 2023-06-12 2023-09-08 之江实验室 Electrical control system, method and device for humanoid robot
CN116713992B (en) * 2023-06-12 2024-07-26 之江实验室 Electrical control system, method and device for humanoid robot

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101493855A (en) * 2009-01-16 2009-07-29 吉林大学 Real-time simulation system for under-driven double-feet walking robot
CN102637036A (en) * 2012-05-08 2012-08-15 北京理工大学 Combined type bionic quadruped robot controller
CN105856243A (en) * 2016-06-28 2016-08-17 湖南科瑞特科技股份有限公司 Movable intelligent robot
KR20160116311A (en) * 2016-09-23 2016-10-07 경북대학교 산학협력단 Method for recognizing continuous emotion for robot by analyzing facial expressions, recording medium and device for performing the method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101493855A (en) * 2009-01-16 2009-07-29 吉林大学 Real-time simulation system for under-driven double-feet walking robot
CN102637036A (en) * 2012-05-08 2012-08-15 北京理工大学 Combined type bionic quadruped robot controller
CN105856243A (en) * 2016-06-28 2016-08-17 湖南科瑞特科技股份有限公司 Movable intelligent robot
KR20160116311A (en) * 2016-09-23 2016-10-07 경북대학교 산학협력단 Method for recognizing continuous emotion for robot by analyzing facial expressions, recording medium and device for performing the method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
于佳: "仿人机器人的关节运动控制系统与传感器系统设计", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
陈贺: "仿人机器人控制系统的研究与开发", 《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑》 *

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110587601A (en) * 2019-08-20 2019-12-20 广西诚新慧创科技有限公司 Control system applied to intelligent inspection robot
CN111161424A (en) * 2019-12-30 2020-05-15 浙江欣奕华智能科技有限公司 Three-dimensional map determination method and determination device
CN111161424B (en) * 2019-12-30 2023-06-02 浙江欣奕华智能科技有限公司 Determination method and determination device for three-dimensional map
CN111414688A (en) * 2020-03-18 2020-07-14 上海机器人产业技术研究院有限公司 Mobile robot simulation system and method based on UNITY engine
CN112025704A (en) * 2020-08-25 2020-12-04 杭州湖西云百生科技有限公司 Real-time distributed robot control method and system based on memory type database
CN114603540A (en) * 2020-12-09 2022-06-10 国核电站运行服务技术有限公司 Nuclear reactor pressure vessel detection manipulator control system
CN113524166A (en) * 2021-01-08 2021-10-22 腾讯科技(深圳)有限公司 Robot control method and device based on artificial intelligence and electronic equipment
CN113183162A (en) * 2021-04-28 2021-07-30 哈尔滨理工大学 Intelligent nursing robot control method and system
CN113485325A (en) * 2021-06-16 2021-10-08 重庆工程职业技术学院 SLAM mapping and autonomous navigation method for underground coal mine water pump house inspection robot
CN114102582A (en) * 2021-11-11 2022-03-01 上海交通大学 Electrical system for super-redundant robot and working method thereof
CN114415653A (en) * 2021-12-01 2022-04-29 中国船舶重工集团公司第七一九研究所 Hybrid control system suitable for unmanned aerial vehicle under water
CN114147721A (en) * 2021-12-15 2022-03-08 东北大学 Robot control system and method based on EtherCAT bus
CN114393563A (en) * 2021-12-21 2022-04-26 昆山市工研院智能制造技术有限公司 Real platform of instructing of operation robot is removed in indoor branch of academic or vocational study
WO2023124326A1 (en) * 2021-12-28 2023-07-06 上海神泰医疗科技有限公司 Robot control method, control device, robot system, and readable storage medium
CN114505853A (en) * 2021-12-30 2022-05-17 爱普(福建)科技有限公司 Remote layered management and control method and system for industrial robot
CN114505853B (en) * 2021-12-30 2023-09-12 爱普(福建)科技有限公司 Remote layered control method and system for industrial robot
CN115026820A (en) * 2022-06-09 2022-09-09 天津大学 Control system and control method for man-machine cooperation assembly robot
CN114932961A (en) * 2022-06-15 2022-08-23 中电海康集团有限公司 Four-footed robot motion control system
CN114932961B (en) * 2022-06-15 2023-10-10 中电海康集团有限公司 Motion control system of four-foot robot
CN116713992A (en) * 2023-06-12 2023-09-08 之江实验室 Electrical control system, method and device for humanoid robot
CN116713992B (en) * 2023-06-12 2024-07-26 之江实验室 Electrical control system, method and device for humanoid robot

Similar Documents

Publication Publication Date Title
CN108858195A (en) A kind of Triple distribution control system of biped robot
Sanna et al. A Kinect-based natural interface for quadrotor control
US9079313B2 (en) Natural human to robot remote control
CN114080583B (en) Visual teaching and repetitive movement manipulation system
JP3994950B2 (en) Environment recognition apparatus and method, path planning apparatus and method, and robot apparatus
US8265791B2 (en) System and method for motion control of humanoid robot
CN112634318B (en) Teleoperation system and method for underwater maintenance robot
CN105867630A (en) Robot gesture recognition method and device and robot system
CN107139179A (en) A kind of intellect service robot and method of work
CN108673501A (en) A kind of the target follower method and device of robot
Tölgyessy et al. The Kinect sensor in robotics education
CN111716365B (en) Immersive remote interaction system and method based on natural walking
CN105945947A (en) Robot writing system based on gesture control and control method of robot writing system
CN115469576B (en) Teleoperation system based on human-mechanical arm heterogeneous motion space hybrid mapping
CN208468393U (en) A kind of Triple distribution control system of biped robot
Chen et al. A human-following mobile robot providing natural and universal interfaces for control with wireless electronic devices
CN106468917A (en) A kind of tangible live real-time video image remotely assume exchange method and system
CN108062102A (en) A kind of gesture control has the function of the Mobile Robot Teleoperation System Based of obstacle avoidance aiding
Maeyama et al. Experiments on a remote appreciation robot in an art museum
JP7309371B2 (en) robot control system
CN117077081A (en) Human body pointing prediction method, device, robot and storage medium
CN114935341B (en) Novel SLAM navigation computation video identification method and device
CN112757274B (en) Human-computer cooperative operation oriented dynamic fusion behavior safety algorithm and system
JP2003266348A (en) Robot device and control method therefor
CN115359222A (en) Unmanned interaction control method and system based on augmented reality

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20181123