Hexapod robot walking based on FCP gait control and deciding contact points

2017 ◽  
Vol 2017 (0) ◽  
pp. 1A1-B10
Author(s):  
Yoshihisa SUZUKI ◽  
Yuki MURATA ◽  
Shinkichi INAGAKI
Keyword(s):  
Hexapod Robot ◽  
Gait Control ◽  
Contact Points

scholarly journals Gait control in a soft robot by sensing interactions with the environment using self-deformation

2016 ◽  
Vol 3 (12) ◽  
pp. 160766 ◽  
Author(s):  
Takuya Umedachi ◽  
Takeshi Kano ◽  
Akio Ishiguro ◽  
Barry A. Trimmer
Keyword(s):  
Sensory Feedback ◽  
Soft Tissues ◽  
Sensory Information ◽  
Gait Pattern ◽  
Soft Robot ◽  
Body Parts ◽  
Gait Control ◽  
Mechanical Responses ◽  
Contact Points ◽  
Propagating Waves

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta . This robot uses deformations of its body to detect changes in friction force on a substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback.

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.

Collision Avoidance Using Contact Information with Multiple Objects by Multi-Leg Robot

2016 ◽  
Vol 28 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Tomohito Takubo ◽  
◽  
Keishi Kominami ◽  
Kenichi Ohara ◽  
Yasushi Mae ◽  
...  
Keyword(s):  
Repulsive Force ◽  
Working Environment ◽  
Hexapod Robot ◽  
Multiple Objects ◽  
Optimal Motion ◽  
Contact Points ◽  
Contact Information ◽  
Walking Motion ◽  
Dynamic Simulator ◽  
Virtual Impedance

[abstFig src='/00280001/02.jpg' width=""300"" text='Optimized multi-point contacting walking' ]In robotics, a walking through motion is complex because of the presence of multipoint contact objects in the working environment of a robot. To simplify the walking through motion of a robot, a virtual impedance field is implemented to the contact points of the robot and an object so that the robot avoids the object passively. The traveling direction of the robot is altered by a virtual repulsive force obtained from the position of the estimated obstacle and the virtual impedance field. The resulting action depends on the parameter of virtual impedance coefficients. Because a combination of parameters includes many things, reinforcement learning is employed to obtain an optimal motion. The optimization of the multipoint contact walking through motion of a robot is finally achieved by evaluating the walking motion while encountering complex obstacles in a dynamic simulator. The motion is implemented on a hexapod robot, and the results demonstrate the effectiveness of the proposed method.

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).

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