scholarly journals Research on Gait control algorithm of Bionic Hexapod Robot System based on Adams and Matlab

2019 ◽  
Vol 332 ◽  
pp. 042036
Author(s):  
Fenghui Xu ◽  
Yongxing Jia ◽  
Zhidong Jia ◽  
Hao Chen ◽  
Xueshuai Guan ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Hexapod Robot ◽  
Robot System ◽  
Gait Control

scholarly journals Analytically founded yaw control algorithm for walking on uneven terrain applied to a hexapod robot

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985799
Author(s):  
Luka Fućek ◽  
Zdenko Kovačić ◽  
Stjepan Bogdan
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Ground Level ◽  
Legged Robot ◽  
Hexapod Robot ◽  
Gait Control ◽  
3 Dimensional ◽  
Yaw Control ◽  
Uneven Terrain ◽  
Gait Phase

This article presents a new control algorithm for the omnidirectional motion of a legged robot on uneven terrain based on an analytical kinematic solution without the use of Jacobians. In order to control the robot easily and efficiently in all situations, a simplified circle-based workspace approximation has been introduced. Foot trajectories for legged robot movement were generated on concentric circular paths around an analytically computed common centre of motion. This systematic motion model, together with new gait control variables that can be changed during legged robot motion, enabled the implementation of a new adaptive gait phase control algorithm, as well as the addition of algorithms for ground-level adaptation, 3-dimensional map-based step adjustment and fusion of all corrections to establish and/or maintain foot contact with the ground. The method being applicable to different legged robot designs was performed and tested on the laboratory prototype of a hexagonal hexapod robot, and the results of the experiments showed the practical value of the proposed adaptive yaw control method (available also as a video supplement).

The Simulation of Robot Control Based on CMAC Neural Network PID Control Algorithm

2013 ◽  
Vol 336-338 ◽  
pp. 659-663
Author(s):  
Jian Li Yu ◽  
Ya Zhou Di ◽  
Lei Yin
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Robot Control ◽  
Control Algorithm ◽  
External Disturbance ◽  
System Model ◽  
Robot System ◽  
System Parameters ◽  
Cmac Neural Network ◽  
Neural Network Pid

According to the problem of nonlinear and uncertainty in robot control, this paper proposes a PID control algorithm based on CMAC neural network model, for the elimination of the influence of uncertainty caused by robot system parameters and external disturbance. The simulation results show that this algorithm can effectively overcome the uncertainties and external disturbance of robot system model, this algorithm has good robustness and stability, its performance is superior to the traditional PID control algorithm.

scholarly journals Research on the Control Principle of “Four Wheels and Hexapod” Robot System

2019 ◽  
Vol 332 ◽  
pp. 042033
Author(s):  
Fenghui Xu ◽  
Yongxing Jia ◽  
Xueshuai Guan ◽  
Tiquan Sun ◽  
Jing Gong ◽  
...  
Keyword(s):  
Hexapod Robot ◽  
Robot System ◽  
Control Principle

scholarly journals Gait Control of Hexapod Robot Based on Field-Programmable Gate Array and Central Pattern Generator

2020 ◽  
Vol 53 (6) ◽  
pp. 931-937
Author(s):  
Tianbo Qiao
Keyword(s):  
Central Pattern Generator ◽  
Field Programmable Gate Array ◽  
Control Method ◽  
Pattern Generator ◽  
Hexapod Robot ◽  
Gait Control ◽  
Field Programmable ◽  
Physical Prototype ◽  
Hardware Description ◽  
Gate Array

This paper attempts to improve the terrain adaptability of hexapod robot through gait control. Firstly, the multi-leg coupling in the tripodal gait of the hexapod robot was modeled by Hopf oscillator. Then, annular central pattern generator (CPG) was adopted to simulate the leg movements of hexapod robot between signals. Furthermore, a physical prototype was designed for the gait control test on field-programmable gate array (FPGA), and the algorithm of the rhythmic output of the model was programmed in Verilog, a hardware description language. Finally, the effectiveness of our gait control method was verified through the simulation on Xilinx. The results show that the phase difference of the CPG network remained stable; the designed hexapod robot moved at about 5.15cm/s stably in a tripodal gait, and outperformed wheeled and tracked robots in terrain adaptation. The research findings lay a solid basis for the design of all-terrain multi-leg robots.

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