Motion-planning Using RRTs for a Swarm of Robots Controlled by Global Inputs

Abstract

Small-scale robots have great potential in medicine, micro-assembly and many other areas. For example, robots containing iron can be steered using the magnetic gradient generated by MRI scanners. Since the gradient is approximately the same everywhere inside the scanner, each robot receives the same input and therefore they all are subjected to the same force. A similar technique can be used with rotating magnetic fields. Each robot receives the same inputs, making motion planning challenging. This paper uses a Rapidly Exploring Random Tree (RRT) to plan paths that deliver multiple robots to goal positions by using obstacles to break the actuation symmetry.