Biologically Inspired Approaches for Locomotion of a Hexapod Robot OSCAR

2011 ◽  
pp. 35-66 ◽  
Author(s):  
Bojan Jakimovski
Keyword(s):  
Hexapod Robot ◽  
Biologically Inspired

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

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.

scholarly journals Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
A. Espinal ◽  
H. Rostro-Gonzalez ◽  
M. Carpio ◽  
E. I. Guerra-Hernandez ◽  
M. Ornelas-Rodriguez ◽  
...  
Keyword(s):  
Neural Network ◽  
Hardware Implementation ◽  
Pattern Generator ◽  
Quadruped Robot ◽  
Spiking Neural Network ◽  
Resource Usage ◽  
Hexapod Robot ◽  
Biologically Inspired ◽  
Robot Locomotion ◽  
Locomotion System

A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To generate these patterns, the SNN is configured with specific parameters (synaptic weights and topologies), which were estimated by a metaheuristic method based on Christiansen Grammar Evolution (CGE). The system has been implemented and validated on two robot platforms; firstly, we tested our system on a quadruped robot and, secondly, on a hexapod one. In this last one, we simulated the case where two legs of the hexapod were amputated and its locomotion mechanism has been changed. For the quadruped robot, the control is performed by the spiking neural network implemented on an Arduino board with 35% of resource usage. In the hexapod robot, we used Spartan 6 FPGA board with only 3% of resource usage. Numerical results show the effectiveness of the proposed system in both cases.

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