Abstract

Autonomous robot manipulators rely heavily on path planning to navigate and regulate their motion. It’s difficult to solve this NP-complete problem in the dynamic location and to find the optimum rerouted based on the new obstacle appears. Swarm intelligence-based PACO (Parallel Ant Colony Optimization) is being used to determine the most efficient and optimal solution for robot path planning in this work. This research examined the use of PACO for autonomous mobile robots’ navigation in dynamic environments. The results of computer simulations of two distinct pheromone re-initialization strategies are discussed and comparative results are portrayed in this paper.

Keywords:Parallel ant colony optimization; Robot path planning; NP complete problem; Heuristic algorithms