Pause-and-Go Self-Balancing Formation Control of Autonomous Vehicles Using Vision and Ultrasound Sensors

In this work, we implement a decentralized and noncooperative state estimation and control algorithm to autonomously balance a team of robots in a circular formation pattern. The group of robots includes a leader periodically moving at a constant steering angle and a set of followers that, by only leveraging intermittent and noisy proximity measurements, independently implement a fully decentralized state estimation control algorithm to determine and adjust their relative position with closest neighbors. The algorithm is conducted in a pause-and-go sequence, where, during the pause, each robot stops to gather and process the information coming from the measurements, estimate the relative phase with respect to the others, and identify its closest pursuant. During the go, each robot accelerates to space from its closest pursuant and then to move at a constant speed when the desired spacing is achieved. The algorithm is tested in an unprecedented experiment on a custom-made low-cost caster-wheeled robotic framework featuring sonar and vision sensors mounted on a rotating platform to estimate the proximity distance to closer neighbors. The control scheme, which does not necessitate cooperation and is capable of coping with uncertain and intermittent sensor feedback data, is shown to be effective in balancing the robot on the circle even when, at a steady state, no feedback sensor data are available.