Authors: Suvranshu Pattanayak; Bibhuti Bhusan Choudhury
Addresses: Department of Production Engineering, Indira Gandhi Institute of Technology, Sarang, 759146, Odisha, India ' Department of Mechanical Engineering, Indira Gandhi Institute of Technology, Sarang, 759146, Odisha, India
Abstract: The latest moves in trajectory planning for autonomous mobile robots are directed towards a popular investigation work. This paper introduces modified particle swarm optimisation technique called as adaptive particle swarm optimisation (APSO) and particle swarm optimisation (PSO) for trajectory length optimisation. For estimating the trajectory length of the robot, nine numbers of obstacles is selected between start and goal point in a static environment. Lastly a comparison is established between these two approaches, to identify the approach that affords shortest trajectory length in a least computation time and shortest possible travel time. Simulation result shows that APSO contributes towards curtail trajectory length at a lesser computational and travel time as compared to PSO.
Keywords: autonomous mobile robot; particle swarm optimisation; PSO; adaptive particle swarm optimisation; APSO.
International Journal of Swarm Intelligence, 2019 Vol.4 No.2, pp.96 - 110
Received: 17 Aug 2018
Accepted: 30 Jan 2019
Published online: 06 Dec 2019 *