Multi-vehicle rover testbed using a new indoor positioning sensor

Abstract

This thesis describes the design and implementation of an indoor multi-rover testbed using a high-precision indoor positioning sensor system. The system model for the rover is derived and used in a Kalman filter that estimates each rover's velocity given the position measurements. These state estimates are then used in high-level path planning and control algorithms. Single and multi-rover tests are performed using single and multi-waypoint path plans. The results from these tests demonstrate the correctness of the system model, estimator, and control algorithms. This testbed serves as a platform for future multi-vehicle coordinated control experiments.