Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning

This paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generation gives us continuous, smooth and optimized path trajectories. Simulation and experimental results demonstrate the effectiveness of the proposed method.

I. Introduction

The scientific and industrial community have devoted much of their effort in creating optimization algorithms to solve global path planning problems. This is due to a growing and general interest of use of mobile robots, car driver, drones and industrial machines in different types of practical proposals [1]–[3]. Much of this work goes into the creation of intelligent, autonomous and mobile robots, particularly proposing new algorithms for motion trajectory generation, obstacle avoidance, position control, energy efficiency, location and navigation [4]–[5].