This paper introduces HOPPY, an open-source, low-cost, robust, and modular kit for robotics education. The robot dynamically hops around a rotating gantry with a fixed base. The kit is intended to lower the entry barrier for studying dynamic robots and legged locomotion with real systems. It bridges the theoretical content of fundamental robotic courses with real dynamic robots by facilitating and guiding the software and hardware integration. This paper describes the topics which can be studied using the kit, lists its components, discusses preferred practices for implementation, presents results from experiments with the simulator and the real system, and suggests further improvements. A simple heuristic-based controller is described to achieve velocities up to 1.7m/s, navigate small objects, and mitigate external disturbances when the robot is aided by a counterweight. HOPPY was utilized as the subject of a semester-long project for the Robot Dynamics and Control course at the University of Illinois at Urbana-Champaign. The positive feedback from the students and instructors about the hands-on activities during the course motivates us to share this kit and continue improving it in the future.

This paper investigates the behavior of a group of autonomous robots evolving in a polygonal environment according to a "move away from the closest neighbor" heuristic. We demonstrate that this distributed coordination algorithm optimizes an aggregate cost function that measures how uniformly distributed are the robots in their environment. Our technical approach based on non-smooth analysis and computational geometry unveils a sphere-packing problem. The algorithm is implemented in a testbed of indoor mobile robots equipped with sonar. We develop novel approaches for improving single point sonar scan performance. These algorithms are then shown to have improved reliability, resolution and speed in distributed environments as compared to other scanning methods.