A Fast Non-dominated Sorting Multi-objective Symbiotic Organism Search Algorithm for Energy Efficient Locomotion of Snake Robot


Baysal Y., Altas I.

COMPUTER SCIENCE AND INFORMATION SYSTEMS, vol.19, no.1, pp.353-378, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 19 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.2298/csis210222067b
  • Journal Name: COMPUTER SCIENCE AND INFORMATION SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Computer & Applied Sciences, INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.353-378
  • Keywords: Energy efficiency, adaptive locomotion, friction condition, optimum gait parameters, symbiotic organism search algorithm, multi-objective optimization, snake robot, OPTIMIZATION
  • Karadeniz Technical University Affiliated: Yes

Abstract

This paper deals with energy efficient locomotion of a wheel-less snake robot. This is very crucial for potential applications of untethered snake robots. The optimum gait parameters for the energy efficient locomotion of the snake robot are obtained with two different multi-objective algorithms based on symbiotic organism search algorithm by considering both minimizing the average power consumption and maximizing the forward velocity of the robot. This paper also investigates the energy efficient locomotion of the snake robot under different environment conditions. The obtained results demonstrate that both proposed methods achieve satisfying stable results regarding power consumption reduction with optimal forward velocity for lateral undulation motion. However, it is seen that fast non-dominated sorting multi-objective symbiotic organism search algorithm provides advantage on obtaining a uniformly distributed solution set with a good diversity only in a single run. This paper is important in terms of presenting useful results for developing efficient motion and environmental adaptability of the snake robot.