A topological implementation for motion planning of a robotic arm

This paper details an intelligent motion planning and control approach for a one-degree of freedom joint of a robotic arm that can be used to implement anthropomorphic robotic hands. This intelligent control method is based on bio-inspired electronic neural networks and contractile artificial muscles implemented with shape memory alloy (SMA) actuators. The spiking neural network (SNN) includes several excitatory neurons that naturally determine the contraction force of the actuators, and unevenly distributed inhibitory neurons that regulate the excitatory activity. To validate the proposed concept, the experiments highlight the motion planning and control of a single-joint robotic arm. The results show that the electronic neural network is able to intelligently activate motion and hold with high precision the mobile link to the target positions even if the arm is slightly loaded. These results are encouraging for the development of improved biologically plausible neural structures that are able to control simultaneously multiple muscles.

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Cartesian space robot manipulator clamping movement in ROS simulation and experiment

Applied Mathematics and Nonlinear Sciences ◽

10.2478/amns.2021.1.00011 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Longtao Mu ◽

Yunfei Zhou ◽

Tiebiao Zhao

Keyword(s):

Motion Planning ◽

Position Control ◽

Robot Manipulator ◽

Robotic Arm ◽

Robot Motion ◽

Robot Arm ◽

Operation System ◽

Model File ◽

Simulation And Experiment ◽

Tool Centre Point

Abstract This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm sorting operation using the top method, to automate the sorting operation and improve the work efficiency of workpiece sorting. Through the ROS MoveIt! module, the sorting pose and movement path of the robotic arm are planned, the inverse kinematics of the sorting robotic arm is solved, and the movement pose characteristics of the sorting robotic arm are analysed. The robot arm model was created using Solidworks software, and the URDF model file of the robot arm was exported through the sw2urdf plugin conversion tool, and the parameters were configured. Based on ROS for 6-degree-of-freedom (DOF) robot motion simulation, random extended tree (RRT) algorithm from open motion planning library (OMPL) is selected. The robot motion planning analysis and sorting manipulator drive UR5 manipulator. The results show that the sorting pose and motion trajectory of the robot arm are determined by controlling the sorting pose of the sorting robot arm, and the maximum radius value of the tool centre point (TCP) rotation of the robot arm and the position of the workpiece are obtained. This method can improve the success rate of industrial sorting robots in grabbing objects. This analysis is of great significance to the research of robots’ autonomous object grabbing.

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Motion Planning of a Robotic Arm using an Adaptive Linear Interpolation Crossover and Variable-Length Move Sequence Genome

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ) ◽

10.1109/hnicem48295.2019.9073378 ◽

2019 ◽

Author(s):

Dino Dominic Ligutan ◽

Jason L. Espanola ◽

Alexander C. Abad ◽

Argel A. Bandala ◽

Elmer P. Dadios

Keyword(s):

Motion Planning ◽

Linear Interpolation ◽

Variable Length ◽

Robotic Arm

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Criterion for Human Arm in Reaching Tasks and Human-like Motion Planning of Robotic Arm

Journal of Mechanical Engineering ◽

10.3901/jme.2015.23.021 ◽

2015 ◽

Vol 51 (23) ◽

pp. 21

Author(s):

Jing ZHAO

Keyword(s):

Motion Planning ◽

Robotic Arm ◽

Reaching Tasks ◽

Human Arm

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PR-RRT*: Motion Planning of 6-DOF Robotic Arm Based on Improved RRT Algorithm

2020 10th Institute of Electrical and Electronics Engineers International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) ◽

10.1109/cyber50695.2020.9279164 ◽

2020 ◽

Author(s):

Yi Liang ◽

Hengyang Mu ◽

Diansheng Chen ◽

Xiaodong Wei ◽

Min Wang

Keyword(s):

Motion Planning ◽

Robotic Arm

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Humanoid motion planning of robotic arm based on human arm action feature and reinforcement learning

Mechatronics ◽

10.1016/j.mechatronics.2021.102630 ◽

2021 ◽

Vol 78 ◽

pp. 102630

Author(s):

Aolei Yang ◽

Yanling Chen ◽

Wasif Naeem ◽

Minrui Fei ◽

Ling Chen

Keyword(s):

Reinforcement Learning ◽

Motion Planning ◽

Robotic Arm ◽

Human Arm

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Development of PC-Based Simulation and Control Platform for a 6-DOF Robotic Arm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.543-547.1397 ◽

2014 ◽

Vol 543-547 ◽

pp. 1397-1400 ◽

Cited By ~ 1

Author(s):

Wen Zhe Wang ◽

Shi Yue Liu ◽

Qing Bo Geng ◽

Qing Fei

Keyword(s):

Motion Planning ◽

Robot Control ◽

Servo Control ◽

Robotic Arm ◽

Kinematic Scheme ◽

Control Card ◽

Point Motion ◽

Real Robot ◽

Point To Point ◽

And Control

This paper developed a 6-DOF (degree of freedom) PC-Based robotic arm system. The system mainly include in software platform and servo control card, servo control card based on microcontroller STC12C5A60S2 was designed to drive the servomotor connected with each joint of robot. The software was implemented by combining MFC with OpenGL. By using the OpenGL functions, the software is able to draw and simulate the 3D kinematic scheme of the robot, it also provides 3D motion planning simulation feature. With the help of simulation in the GUI, users can visualize the manipulator motion planning. Furthermore, user also can control the real robotic arm through this software. Finally, point-to-point motion and continuous path motion are all tested in simulation and real robot control. The entire system has been successfully implemented.

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