Recent Metaheuristics Analysis of Path Planning Optimaztion Problems

摘要

In this paper we present different computational intelligent algorithms for solving piano mover problems also known as robot path planning problems. Path planning is one of the major problems in robotics technology. Since robots have no intelligent means of understanding its environment, it's usually fundamental to develop an obstacle free and costefficient path capable of navigating the robot within its environment. In line with this, we present a method for obstacle free robot path planning in an intermediate search environment using a novel Smell Agent Optimization (SAO), Particle Swarm Optimization (PSO) and Smell Detection Agent (SDA) algorithms. We implemented our proposed method in MATLAB R2019a simulation environment. Results showed that our proposed methods can find an obstacle free path efficiently with low computational cost.