CN110587603A - Pose self-induction joint module motion control system based on multi-sensor data fusion - Google Patents
Pose self-induction joint module motion control system based on multi-sensor data fusion Download PDFInfo
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- CN110587603A CN110587603A CN201910838473.1A CN201910838473A CN110587603A CN 110587603 A CN110587603 A CN 110587603A CN 201910838473 A CN201910838473 A CN 201910838473A CN 110587603 A CN110587603 A CN 110587603A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1612—Programme controls characterised by the hand, wrist, grip control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1633—Programme controls characterised by the control loop compliant, force, torque control, e.g. combined with position control
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Abstract
The invention discloses a pose self-induction joint module motion control system based on multi-sensor data fusion, which consists of a controller module, a power driving module, a detection feedback module and an execution module, wherein the controller module is connected with the power driving module, the power driving module is connected with the execution module, and the execution module is connected with the controller module through the detection feedback module. The multi-sensor data fusion pose self-induction joint module motion control system provided by the invention can realize the calculation of the space pose of each joint, thereby compensating the pose of the joint in real time in the control process and improving the overall control precision. The invention carries out fusion processing on the information of a plurality of sensors, realizes flexible control, increases the redundancy of the actuator and further improves the use safety of the actuator.
Description
Technical Field
The invention belongs to the field of robot joint motion control, and particularly relates to a pose self-induction joint module motion control system based on multi-sensor data fusion.
Background
Along with the rapid development of intelligent manufacturing technology, the demand of the robot at home and abroad is higher and higher, and the traditional industrial robot cannot well realize human-computer cooperation due to the problems of large volume, difficult transportation, complex teaching and safety. Therefore, the cooperative robot which is miniaturized, modularized, reconfigurable and high in safety gradually becomes a hot spot in the robot industry. The joint module of the cooperative robot is a core unit of the whole cooperative robot system, directly determines the kinematics, dynamics and control performance of the whole cooperative robot system, and is the research and development focus of the next generation cooperative robot system.
The existing cooperative robot joint module mainly considers the control performance of a single robot module and mainly realizes the position and moment control and the like of the joint module. Therefore, when the joint arms are integrated, the situation that each joint deviates from the theoretical position under the action of the self weight and the load of the robot cannot be known, the error is difficult to correct, the problem of inaccurate spatial positioning is likely to occur, and the service performance of the cooperative robot is seriously influenced. The pose precision detection executed at the tail end of the cooperative robot needs to be completed by means of third-party detection equipment, the use is complex, the size is increased, and the advantages of the cooperative robot are seriously influenced.
Disclosure of Invention
In order to enable the cooperative robot to have an actuator end pose correction function, the invention provides a pose self-induction joint module motion control system based on multi-sensor data fusion, which can realize real-time monitoring and feedback compensation of the spatial position of the cooperative robot integrated by the joint module.
In order to achieve the above-mentioned problems, the present invention provides the following solutions:
a pose self-induction joint module motion control system based on multi-sensor data fusion is composed of a controller module, a power driving module, a detection feedback module and an execution module, wherein the controller module is connected with the power driving module, the power driving module is connected with the execution module, and the execution module is connected with the controller module through the detection feedback module. The invention also provides a joint module structure suitable for the motion control system, which integrates the motion control system into a joint module for use, wherein the joint module comprises key components such as a harmonic reducer, a torque motor, an incremental encoder, a bearing, an absolute encoder, a detection feedback circuit board, a driving circuit board, a control circuit board, a shell and the like.
The pose self-induction joint module motion control system based on multi-sensor data fusion is characterized in that: the controller module comprises a control chip, an external circuit, a communication circuit and the like, wherein the peripheral circuit and the communication circuit are connected with the control chip and are used for providing electric energy and corresponding peripheral interfaces. The controller module is used for receiving the signal of the detection feedback module, judging the running state of the execution module, resolving the spatial pose, sending a control signal to the power driving module and compensating the difference value between the actual pose and the theoretical pose.
The power driving module comprises an isolating circuit, a power driving circuit and a three-phase inverter circuit, the isolating circuit receives signals of the control module, transmits the signals to the power driving circuit after isolation, transmits the signals after power amplification to the three-phase inverter circuit to generate driving control signals, and drives the torque motor to rotate.
The detection feedback module consists of an incremental encoder, an absolute encoder and a detection circuit board, wherein the detection circuit board comprises a current sensor, a voltage sensor, a nine-axis sensor, a temperature sensor and a torque sensor, and the sensors on the detection circuit board are integrated together, so that the occupied space is effectively reduced; the incremental encoder is used for acquiring speed and electrical angle information of the joint motor, the absolute encoder is used for acquiring position information of the actuator, the current sensor is used for acquiring phase current information of the actuator motor, the voltage sensor is used for acquiring bus voltage information of the actuator motor, the nine-axis sensor is used for acquiring space pose information of the joint motor, the temperature sensor is used for acquiring temperature information of the actuator module, and the torque sensor is used for acquiring torque information borne by the actuator module;
the actuator module comprises the main components of the harmonic reducer, the frameless motor, the bearing and the like, the harmonic reducer is connected with the frameless torque motor through the coupler, and the components of the bearing and the like play a role in positioning and supporting. And the actuator module is used for transmitting the motion information from the controller module.
The pose self-induction joint module motion control system based on multi-sensor data fusion is characterized in that: the nine-axis sensor is a self-calibration nine-axis data fusion Inertial Measurement Unit (IMU) (comprising an accelerometer (three axes), a gyroscope (three axes) and a magnetometer (three axes)), and is integrated with other detection circuits on the same circuit board, so that the circuit board and the whole space are reduced, the integrated circuit board is installed near the rear end cover of the actuator, and the interference of a motor magnetic field on the integrated circuit board is reduced.
The pose self-induction joint module motion control system based on multi-sensor data fusion is characterized in that: the control chip of the controller module is a DSP, and the nine-axis sensor firstly calibrates noise, size deviation and axis deviation when being powered on and used each time; and transmitting the acquired angular velocity, acceleration and magnetic force value information to a control chip in real time in the operation process, and performing subsequent processing in the control chip.
The pose self-induction joint module motion control system based on multi-sensor data fusion is characterized in that: the control chip performs fusion processing on the acquired sensor information; the acceleration/magnetometer has high-frequency noise, the instantaneous values of the high-frequency noise and the high-frequency noise are not accurate enough, and the calculated posture can oscillate; the gyroscope has low-frequency noise, the obtained angular velocity at each moment is relatively accurate, the rotation angle (attitude) can be obtained by using integration, but the integration can accumulate errors and a drift phenomenon can occur. The characteristics of the acceleration/magnetometer and the gyroscope on the frequency domain are complementary, the data of the three sensors can be fused, and the accuracy and the dynamic characteristics of the system are improved, so that the Quaternion Quaternion can be adopted for attitude calculation. Meanwhile, the information of the absolute encoder is collected, the spatial position of the actuator joint is calculated, the position information of the two sensors is fused, the spatial pose of the end actuator can be more accurately determined, the full closed-loop real-time feedback compensation control can be further performed on the spatial pose of the whole mechanical arm, and the real-time pose compensation of the mechanical arm under the load condition is realized. Common nine-axis data fusion algorithms include high-low-pass complementary filtering, extended kalman filtering EKF, Mahony filtering, and the like, and can be selected according to different purposes in actual situations.
The pose self-induction joint module motion control system based on multi-sensor data fusion is characterized in that: and a torque sensor of the detection feedback module, a current sensor and acceleration information are fused and are jointly used for judging the torque borne by the actuator module, so that the flexible control of the cooperative robot can be realized.
Compared with the prior art, the invention has the following advantages: the multi-sensor data fusion pose self-induction joint module motion control system provided by the invention can realize the calculation of the space pose of each joint, thereby compensating the pose of the joint in real time in the control process and improving the overall control precision. Meanwhile, the information of a plurality of sensors is subjected to fusion processing, flexible control is realized, the redundancy of the actuator is increased, and the use safety of the actuator is further improved.
Drawings
FIG. 1 is a block diagram of a pose self-induction joint module motion control system based on multi-sensor data fusion;
FIG. 2 is a schematic structural diagram of a pose self-induction joint module based on multi-sensor data fusion according to the present invention;
in the figure, a controller module 1, a power driving module 2, a detection feedback module 3, an actuator module 4, a harmonic reducer 5, a torque motor 6, an incremental encoder 7, a bearing 8, an absolute encoder 9, a detection circuit board 10, a driving circuit board 11, a control circuit board 12 and a shell 13.
FIG. 3 is a flow chart of a multi-sensor data fusion algorithm of the present invention;
Detailed Description
The invention will be further elucidated and described with reference to the drawings and the detailed description.
The invention discloses a pose self-induction joint module motion control system based on multi-sensor data fusion, which is composed of a controller module 1, a power driving module 2, a detection feedback module 3 and an execution module 4, and also discloses a joint module structure schematic diagram applicable to the motion control system, and mainly comprises a harmonic reducer 5, a torque motor 6, an incremental encoder 7, a bearing 8, an absolute encoder 9, a detection feedback circuit board 10, a driving circuit board 11, a control circuit board 12, a shell 13 and other key components.
In a specific example of the present invention, the controller module 1 mainly comprises the control circuit board 12, and includes a control chip, an external circuit, a communication interface circuit, and the like, and is mainly responsible for receiving the signal of the detection feedback module 3, determining the operating state of the actuator module 4, resolving the spatial pose thereof, and sending a control signal to the power driving module 2. The power driving module 2 mainly comprises the driving circuit board 11, mainly comprises an isolation circuit, a power driving module and a three-phase inverter circuit, and is mainly responsible for receiving a driving control signal, generating a driving circuit and driving a motor. The detection feedback module 3 is composed of the incremental encoder 7, an absolute encoder 9 and a detection circuit board 10, wherein the incremental encoder 7 is used for acquiring speed and electrical angle information of the joint motor, the absolute encoder 9 is used for acquiring position information of the actuator, and the detection circuit board 10 comprises a current sensor, a voltage sensor, a nine-axis sensor, a temperature sensor and a torque sensor; the current sensor is used for collecting phase current information of the actuator motor, the voltage sensor is used for collecting bus voltage information of the actuator motor, the nine-axis sensor is used for collecting space pose information of the joint motor, the temperature sensor is used for collecting temperature information of the actuator module, and the torque sensor is used for collecting torque information borne by the actuator module. The actuator module 4 executes the motion information sent by the controller module by the main components such as the harmonic reducer 5, the frameless motor 6, the input/output shaft, the bearing and the like.
In one embodiment of the present invention, the nine-axis sensor in the detection feedback module 3 is a self-calibrating nine-axis data-fused Inertial Measurement Unit (IMU) (including accelerometer (three axes), gyroscope (three axes), and magnetometer (three axes)), and is integrated with other detection circuits on the same circuit board, so as to reduce the circuit board and the overall space, and is more applicable to a highly integrated actuator module, and the integrated circuit board is installed near the actuator rear end cover to reduce the interference of the motor magnetic field to the actuator.
In a specific example of the present invention, the control chip of the controller module 1 is a DSP, and the nine-axis sensor IMU first performs calibration of noise, dimensional deviation, and axis deviation at each power-on use; and in the operation process, the acquired angular velocity, acceleration and magnetic force value information is connected with the main control chip through a serial port, and subsequent processing is carried out in the control chip.
In a specific example of the present invention, the control chip of the controller module 1 performs fusion processing on the acquired sensor information; the acceleration/magnetometer has high-frequency noise, the instantaneous values of the high-frequency noise and the high-frequency noise are not accurate enough, and the calculated posture can oscillate; the gyroscope has low-frequency noise, the obtained angular velocity at each moment is relatively accurate, the rotation angle (attitude) can be obtained by using integration, but the integration can accumulate errors and a drift phenomenon can occur. The characteristics of the acceleration/magnetometer and the gyroscope on the frequency domain are complementary, the data of the three sensors can be fused, the precision and the dynamic characteristics of the system are improved, and the Quaternion Quaternion is adopted for attitude calculation. Meanwhile, the information of the absolute encoder is collected, the spatial position of the actuator joint is calculated, the pose of the actuator module is calculated by using an extended Kalman filtering data fusion algorithm, and then the full closed-loop real-time feedback compensation control can be carried out on the spatial pose of the whole mechanical arm, so that the real-time pose compensation of the mechanical arm under the condition of load is realized.
When the full-closed-loop real-time feedback compensation control system is used, the pose information of the actuator module is solved by adopting a low-pass complementary filtering algorithm, and meanwhile, the spatial pose of the end actuator can be more accurately determined by fusing the position information of the encoder and the pose information of the nine-axis sensor, so that the full-closed-loop real-time feedback compensation control can be carried out on the spatial pose of the whole mechanical arm, and the real-time pose compensation of the mechanical arm under the condition of load is realized.
In a specific example of the present invention, the torque sensor of the detection feedback module 3, the current sensor and the acceleration information are fused and used together to determine the torque applied to the actuator module, so that the flexible control and the collision detection of the cooperative robot can be realized.
The above-described embodiment is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Various changes and modifications may be made by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present invention. Therefore, the technical solutions obtained by means of equivalent substitution or equivalent transformation are all within the protection scope of the present invention without departing from the concept of the present invention.
Claims (10)
1. Position appearance self-induction joint module motion control system based on multisensor data fusion, its characterized in that: the joint module motion control system is composed of a controller module, a power driving module, a detection feedback module and an execution module, wherein the controller module is connected with the power driving module, the power driving module is connected with the execution module, and the execution module is connected with the controller module through the detection feedback module.
2. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the controller module comprises a control chip, an external circuit and a communication circuit, wherein the peripheral circuit and the communication circuit are connected with the control chip and are used for providing electric energy and corresponding peripheral interfaces; the controller module is used for receiving the signal of the detection feedback module, judging the running state of the execution module, resolving the spatial pose, sending a control signal to the power driving module and compensating the difference value between the actual pose and the theoretical pose.
3. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the power driving module comprises an isolating circuit, a power driving circuit and a three-phase inverter circuit, the isolating circuit receives signals of the control module, transmits the signals to the power driving circuit after isolation, transmits the signals after power amplification to the three-phase inverter circuit to generate driving control signals, and drives the torque motor to rotate.
4. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the detection feedback module consists of an incremental encoder, an absolute encoder and a detection circuit board, wherein the detection circuit board comprises a current sensor, a voltage sensor, a nine-axis sensor, a temperature sensor and a torque sensor, and the sensors on the detection circuit board are integrated together; the incremental encoder is used for acquiring speed and electrical angle information of the joint motor, the absolute encoder is used for acquiring position information of the actuator, the current sensor is used for acquiring phase current information of the actuator motor, the voltage sensor is used for acquiring bus voltage information of the actuator motor, the nine-axis sensor is used for acquiring space pose information of the joint motor, the temperature sensor is used for acquiring temperature information of the actuator module, and the torque sensor is used for acquiring torque information borne by the actuator module.
5. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the actuator module comprises the harmonic reducer, a frameless motor and a bearing, the harmonic reducer is connected with the frameless torque motor through a coupler, and the bearing plays a role in positioning and supporting; and the actuator module is used for transmitting the motion information from the controller module.
6. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the nine-axis sensor is an inertial measurement element with self-calibration nine-axis data fusion, is integrated with other detection circuits on the same circuit board, and is mounted near the rear end cover of the actuator.
7. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the control chip of the controller module is a DSP, and the nine-axis sensor firstly calibrates noise, size deviation and axis deviation when being powered on and used each time; and transmitting the acquired angular velocity, acceleration and magnetic force value information to a control chip in real time in the operation process, and performing subsequent processing in the control chip.
8. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the control chip performs fusion processing on the acquired sensor information; the gyroscope can obtain the rotation angle by using integration; the characteristics of the acceleration/magnetometer and the gyroscope on the frequency domain are complementary, the data of the three sensors are fused, the precision is improved, and the dynamic characteristics of the system are solved by adopting a Quaternion Quaternion; meanwhile, the information of the absolute encoder is collected, the spatial position of the actuator joint is calculated, the position information of the two sensors is fused, the spatial pose of the end actuator can be more accurately determined, the full closed-loop real-time feedback compensation control is further performed on the spatial pose of the whole mechanical arm, and the real-time pose compensation of the mechanical arm under the load condition is realized.
9. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: and a torque sensor of the detection feedback module, a current sensor and acceleration information are fused and are jointly used for judging the torque borne by the actuator module, so that the flexible control of the cooperative robot is realized.
10. The pose self-induction joint module motion control system based on multi-sensor data fusion of claim 1, characterized in that: the detection feedback module consists of the incremental encoder, an absolute encoder and a detection circuit board, wherein the incremental encoder is used for acquiring the speed and the electrical angle information of the joint motor, and the absolute encoder is used for acquiring the position information of the actuator;
the current sensor is used for collecting phase current information of the actuator motor, the voltage sensor is used for collecting bus voltage information of the actuator motor, the nine-axis sensor is used for collecting space pose information of the joint motor, the temperature sensor is used for collecting temperature information of the actuator module, and the torque sensor is used for collecting torque information borne by the actuator module.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111756272A (en) * | 2020-07-09 | 2020-10-09 | 四川航天烽火伺服控制技术有限公司 | Double-output servo mechanism |
| CN114505854A (en) * | 2022-01-11 | 2022-05-17 | 北京盈迪曼德科技有限公司 | Multi-sensor data detection processing method and device and robot |
| CN117249811A (en) * | 2023-11-20 | 2023-12-19 | 中国建筑一局(集团)有限公司 | Distributed inclination monitoring system and method for super high-rise building |
| CN117325183A (en) * | 2023-11-21 | 2024-01-02 | 深圳职业技术大学 | Modularized mechanical arm control method based on pose transmission rod |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103170979A (en) * | 2013-02-06 | 2013-06-26 | 华南理工大学 | Online robot parameter identification method based on inertia measurement instrument |
| CN103792896A (en) * | 2012-11-02 | 2014-05-14 | 刘胜 | Integrated heavy-machinery intelligent cantilever crane control system and control method |
| KR20150121935A (en) * | 2014-04-22 | 2015-10-30 | 부산대학교 산학협력단 | A New MEMS Gyro Approach Using LSM for Mobile Robot Heading Detection |
| CN205066775U (en) * | 2015-09-17 | 2016-03-02 | 泉州装备制造研究所 | High accuracy movement track detection device |
| CN107160390A (en) * | 2017-05-16 | 2017-09-15 | 中国科学院沈阳自动化研究所 | It is a kind of to control integral control system for the robot that cooperates |
| CN108972567A (en) * | 2017-05-31 | 2018-12-11 | 西门子（中国）有限公司 | Mechanical arm collision avoidance system, method and storage medium |
| CN109109018A (en) * | 2018-09-13 | 2019-01-01 | 微创（上海）医疗机器人有限公司 | Device and method, mechanical arm and the medical robot of equipment working state are sensed in detection mechanical arm |
| CN109129492A (en) * | 2018-11-07 | 2019-01-04 | 宁波赛朗科技有限公司 | A kind of industrial robot platform that dynamic captures |
| CN109262614A (en) * | 2018-10-12 | 2019-01-25 | 清华大学深圳研究生院 | A kind of joint of robot mould group kinetic control system and its method |
| CN109394344A (en) * | 2018-12-29 | 2019-03-01 | 苏州康多机器人有限公司 | A kind of data self calibration main manipulator |
| CN109445416A (en) * | 2018-10-31 | 2019-03-08 | 中国科学院合肥物质科学研究院 | A kind of highly integrated joint control system of Multi-sensor Fusion |
| CN110076776A (en) * | 2019-04-30 | 2019-08-02 | 南京云图机器人科技有限公司 | A method of using inertia device hoisting machine people's stability |
-
2019
- 2019-09-05 CN CN201910838473.1A patent/CN110587603A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103792896A (en) * | 2012-11-02 | 2014-05-14 | 刘胜 | Integrated heavy-machinery intelligent cantilever crane control system and control method |
| CN103170979A (en) * | 2013-02-06 | 2013-06-26 | 华南理工大学 | Online robot parameter identification method based on inertia measurement instrument |
| KR20150121935A (en) * | 2014-04-22 | 2015-10-30 | 부산대학교 산학협력단 | A New MEMS Gyro Approach Using LSM for Mobile Robot Heading Detection |
| CN205066775U (en) * | 2015-09-17 | 2016-03-02 | 泉州装备制造研究所 | High accuracy movement track detection device |
| CN107160390A (en) * | 2017-05-16 | 2017-09-15 | 中国科学院沈阳自动化研究所 | It is a kind of to control integral control system for the robot that cooperates |
| CN108972567A (en) * | 2017-05-31 | 2018-12-11 | 西门子（中国）有限公司 | Mechanical arm collision avoidance system, method and storage medium |
| CN109109018A (en) * | 2018-09-13 | 2019-01-01 | 微创（上海）医疗机器人有限公司 | Device and method, mechanical arm and the medical robot of equipment working state are sensed in detection mechanical arm |
| CN109262614A (en) * | 2018-10-12 | 2019-01-25 | 清华大学深圳研究生院 | A kind of joint of robot mould group kinetic control system and its method |
| CN109445416A (en) * | 2018-10-31 | 2019-03-08 | 中国科学院合肥物质科学研究院 | A kind of highly integrated joint control system of Multi-sensor Fusion |
| CN109129492A (en) * | 2018-11-07 | 2019-01-04 | 宁波赛朗科技有限公司 | A kind of industrial robot platform that dynamic captures |
| CN109394344A (en) * | 2018-12-29 | 2019-03-01 | 苏州康多机器人有限公司 | A kind of data self calibration main manipulator |
| CN110076776A (en) * | 2019-04-30 | 2019-08-02 | 南京云图机器人科技有限公司 | A method of using inertia device hoisting machine people's stability |
Non-Patent Citations (1)
| Title |
|---|
| 张洋 等: "《正点原子教你学嵌入式系统丛书 STM32F7原理与应用 HAL库版 下》", 30 June 2017 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111756272A (en) * | 2020-07-09 | 2020-10-09 | 四川航天烽火伺服控制技术有限公司 | Double-output servo mechanism |
| CN114505854A (en) * | 2022-01-11 | 2022-05-17 | 北京盈迪曼德科技有限公司 | Multi-sensor data detection processing method and device and robot |
| CN117249811A (en) * | 2023-11-20 | 2023-12-19 | 中国建筑一局(集团)有限公司 | Distributed inclination monitoring system and method for super high-rise building |
| CN117249811B (en) * | 2023-11-20 | 2024-03-29 | 中国建筑一局(集团)有限公司 | Distributed inclination monitoring system and method for super high-rise building |
| CN117325183A (en) * | 2023-11-21 | 2024-01-02 | 深圳职业技术大学 | Modularized mechanical arm control method based on pose transmission rod |
| CN117325183B (en) * | 2023-11-21 | 2024-06-14 | 深圳职业技术大学 | Modularized mechanical arm control method based on pose transmission rod |
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Application publication date: 20191220 |