A Constraint Optimization path planning for Dynamic Environment

Abstract

Optimal path planning is a major challenge for the operation of autonomous unmanned ground vehicles. In dynamic mobile path planning, the goal is to find a collision-free path for a robot from an initial position to a goal position in an environment with obstacles. However, in a dynamic environment, the challenge is bigger than static. In this paper, a modified ABC and an adaptive constraint PSO algorithm are proposed to deal with the dynamic environment; the algorithms were chosen to have a good balance between exploration and exploitation, with a penalty function used to have a collision-free path.