Hulas, J and Zhou, C orcid.org/0000-0002-6677-0855 (2020) Improving Quadrupedal Locomotion on Granular Material Using Genetic Algorithm. In: UKRAS20 Conference: “Robots into the real world” Proceedings. UKRAS20 Conference: “Robots into the real world”, 17 Apr 2020, University of Lincoln (virtual). UK-RAS Network , pp. 33-34.
Abstract
This paper describes process of generating a stable gait for a quadruped robot on granular material such as sand. To achieve this goal a simulated environment was created, to model the kinematics and dynamics of the robot. Genetic algorithm was used as a gait generation technique. The simulation model of Laikago was built in MATLAB and Simscape. The contact model between the foot and ground, was based on existing results from sand penetration testing. The genetic algorithms optimised the joint space trajectory, to evaluate of the gait performance on granular terrain. The proposed method required to first create a simulation constrained to planar motion to simplify the problem. The 2D gait was then used as the initial guess for the optimisation in 3D simulation and allowed for creation of an acceptable gait. The final gait has demonstrated the effectiveness of the proposed approach for quadruped robot walking on granular terrain.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | quadruped robot, genetic algorithm, legged robot, locomotion |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Apr 2020 12:47 |
Last Modified: | 22 Apr 2024 15:49 |
Published Version: | https://www.ukras.org.uk/publications/ras-proceedi... |
Status: | Published |
Publisher: | UK-RAS Network |
Identification Number: | 10.31256/Qs1Ub7E |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159476 |