Output Feedback Formation Control of a School of Robotic Fish with Artificial Lateral Line Sensing

Abstract

This paper presents an estimation and control framework to stabilize the parallel motion of a school of robotic fish using sensory feedback. Each robot is modeled as a constant speed, planar, self-propelled particle that produces a flowfield according to a dipole potential flow model. An artificial lateral line system senses pressure fluctuations at several locations along each robot's body. The equations of motion and measurement model are formulated in a path frame that translates and rotates with each robot's position and velocity, respectively. A particle filter estimates the relative position and heading of other nearby robots. The resulting estimate drives a Lyapunov-based formation controller to synchronize the headings of the robots and achieve a parallel formation. Numerical simulations illustrate the proposed approach.