A novel IPSO technique for path navigation and obstacle avoidance. (9th March 2022)

• Record Type: Journal Article
• Authors: Mukherjee, Subhradip; Kumar, Rajagopal; Bhattacharjee, Rituraj
• Is Part Of: International journal of system of systems engineering. Volume 11:Number 3/4(2021)
• Page Start: 430
• Page End: 442
• Publication Date: 2022-03-09
• Subjects: path navigation -- autonomous vehicle -- IPSO -- improved particle swarm optimisation -- fitness function -- simulation time -- MATLAB; 003.71
• Languages: English
• ISSNs: 1748-0671

Abstract

Path navigation using meta-heuristic optimisation is a popular research topic in the field of autonomous vehicle path planning. In this paper, an improved particle swarm optimisation (IPSO) technique has been presented for unmanned vehicle path navigation which is the enhanced version of existing PSO technique. IPSO is used to solve the convergence speed problem which is a general practice in optimisation algorithms. The modified fitness function of the proposed algorithm is designed in such a manner that causes to converge the algorithm fast. IPSO technique is dependent upon the working of modified fitness function for the path optimisation in an unknown environment. After several iterations, the best cost is computed which is utilised to find the optimised path in mobile robot path navigation. The simulation results clearly indicate that IPSO is competent enough when compared with the existing optimisation methods (genetic algorithm, invasive weed optimisation (IWO)).