Multi-objective path planning optimization with moving target based on bat algorithm

Abstract

Path planning algorithms is the most significant area in the robotics field. Path Planning (PP) can be defined as the process of determining the most appropriate navigation path before a mobile robot moves. The goal of optimization of PP is to find a path that is close to or optimal path. Multi-objective optimization (MOO) is concerned with finding the best solution values that satisfy multiple objectives, such as shortness, smoothness, and safety. MOO present the challenge of making decisions while balancing these contradictory issues through compromise (tradeoff). As a result, there is no single solution appropriate for all purposes in MOO, but rather a range of solutions. This paper the problem of PP is investigated with path length, security and smoothness objectives for autonomous mobile robots in dynamic environment with moving target. The proposed approach based on Bat algorithm (BA). The proposed solution is tested in a number of simulations with varying scenarios. The simulation results show that multi objective can be achieved efficiently in a dynamic environment which proves its effectiveness.