Kinematic gait and foot trajectory generation for a biologically-inspired autonomous hexapod robot

1996 ◽  
Author(s):  
M.J. Randall
Keyword(s):  
Trajectory Generation ◽  
Hexapod Robot ◽  
Biologically Inspired ◽  
Foot Trajectory

Real-Time Online Feet Trajectory Generation Method for Hexapod Robot

2015 ◽  
Vol 220-221 ◽  
pp. 148-152
Author(s):  
Tomas Luneckas ◽  
Mindaugas Luneckas ◽  
Dainius Udris
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Trajectory Generation ◽  
Electromechanical System ◽  
Hexapod Robot ◽  
Walking Robot

Hexapod walking robot is a complex electromechanical system with many degrees of freedom. Six legs ensure robot’s stability as at least three legs are always on the ground but require more effort in order to synchronize them for a successful locomotion. In this paper, we present a method that allows calculate feet trajectories in real-time and online. This method enables to select different gaits and their parameters.

scholarly journals Energy-based control for a biologically inspired hexapod robot with rolling locomotion

2015 ◽  
Vol 1 (2) ◽  
pp. 125-133 ◽  
Author(s):  
Takuma Nemoto ◽  
Rajesh Elara Mohan ◽  
Masami Iwase
Keyword(s):  
Hexapod Robot ◽  
Biologically Inspired ◽  
Rolling Locomotion

A Swing-foot Trajectory Generation Method For Biped Walking*

2021 ◽  
Author(s):  
Huanzhong Chen ◽  
Xuechao Chen ◽  
Zhangguo Yu ◽  
Chencheng Dong ◽  
Qingqing Li ◽  
...  
Keyword(s):  
Trajectory Generation ◽  
Biped Walking ◽  
Foot Trajectory

scholarly journals A biologically inspired approach to feasible gait learning for a hexapod robot

2010 ◽  
Vol 20 (1) ◽  
pp. 69-84 ◽  
Author(s):  
Dominik Belter ◽  
Piotr Skrzypczyński
Keyword(s):  
Fitness Function ◽  
Search Space ◽  
Walking Robots ◽  
Hexapod Robot ◽  
Walking Robot ◽  
Insect Behaviour ◽  
Biologically Inspired ◽  
Gait Patterns ◽  
Gait Learning ◽  
The Given

A biologically inspired approach to feasible gait learning for a hexapod robotThe objective of this paper is to develop feasible gait patterns that could be used to control a real hexapod walking robot. These gaits should enable the fastest movement that is possible with the given robot's mechanics and drives on a flat terrain. Biological inspirations are commonly used in the design of walking robots and their control algorithms. However, legged robots differ significantly from their biological counterparts. Hence we believe that gait patterns should be learned using the robot or its simulation model rather than copied from insect behaviour. However, as we have foundtahula rasalearning ineffective in this case due to the large and complicated search space, we adopt a different strategy: in a series of simulations we show how a progressive reduction of the permissible search space for the leg movements leads to the evolution of effective gait patterns. This strategy enables the evolutionary algorithm to discover proper leg co-ordination rules for a hexapod robot, using only simple dependencies between the states of the legs and a simple fitness function. The dependencies used are inspired by typical insect behaviour, although we show that all the introduced rules emerge also naturally in the evolved gait patterns. Finally, the gaits evolved in simulations are shown to be effective in experiments on a real walking robot.

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