Smooth Trajectory Planning for Autonomous Leader-Follower Robots

Abstract

Path planning is a key factor that determines how well a robotic vehicle performs in executing automated formations and maneuvers as in multi-vehicle platooning and selforganizing leader following with safe and graceful movements. Many types of pathplanning schemes have been employed in the autonomous robotics and driving systems. In this paper, we will focus on the application of a smooth path-planning (SPP) algorithm that produces simple-to-implement robotic maneuvers. The algorithm is derived from using a well-established Lyapunov stability criterion and a clever dynamical control synthesis. We show that the SPP can be adapted to many autonomous guidance scenarios. Simulations show that the SPP resulted in autonomous behaviors similar to that parallel those of human or animal actions. The paper presents results using Matlab simulations as well as Gazebo animation. The results will provide a foundation for an implementation of SPP on actual robotic vehicles.