Hybridization of IWO and IPSO for mobile robots navigation in a dynamic environment

Abstract

This paper has given a fresh approach of hybridization of invasive weed optimization (IWO) with improved particle swarm optimization (IPSO) to obtain the optimal path for each robot in multi-robots system in a non-stationary environment. The main emphasis of the algorithm is to lessen the path length and time taken by all robots to arrive at the respective destined target in the cluttered environment. Each robot takes independent decisions of their own to evaluate the next positions from their current position in the global map using proposed hybrid IWO-IPSO. The proposed approach embedded the spatial dispersion method of IWO with motion mechanism of IPSO called IWO-IPSO. The main aim of the hybridization is to maintain a good balance between intensification and diversification and avoid local minima value because of adopting co-evolutionary techniques to update the velocity and particle positions with IPSO simultaneously. The effectiveness of the algorithm has been validated through simulation and real platform. Finally, the experimental and simulation results of IWO-IPSO for multi-robot path planning are weighed against with results obtained by IPSO, IWO in a analogous environment to make sure the integrity of the algorithm is maintained. The results obtained from simulation on top of Khepera environment justifies that, the proposed IWO-IPSO performs superiorly than IPSO and IWO with respect to arrival time, energy utilization during travel of path, optimal path length and deviation of path.

Keywords

• Multi robot
• Trajectory path travelled
• Trajectory path deviation
• IWO
• IPSO
• Path planning