This paper presents a modular and reconfigurable robot for multiple locomotion modes based on reconfigurable modules. Each mode consists of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recover ability from failures. The paper demonstrates this solution by the Superbot robot that combines advantages from MTRAN, CONRO and others. Experimental results, both in real robots and in simulation, have shown the validity of the approach and demonstrated the movements of forward, backward, turn, sidewinder, maneuver, and travel on batteries up to 500 meters on a flat terrain. In physics-based simulation, Superbot can perform as snake, caterpillar, insect, spider, rolling track, H-walker, etc., and move 1.0 meter/second on flat terrain with less than 6 W/module, and climb slopes of no less 40 degrees

We present a distributed controller for the center of mass of a modular robot. This is useful for locomotion of a modular robot over uneven and unknown terrain. By controlling the center of mass, a robot can prevent itself from falling over. We present a distributed and decentralized algorithm that computes the mass properties of the robot. Additionally, each module also computes the mass properties of the modules that are directly or indirectly connected to each of its connectors. With this information, each module can independently steer the center of mass towards a desired position by adjusting its joint positions. We present simulation results that show the feasibility of the approach

In this paper, we introduce and describe the notion of a robotic enzyme, and how it can use properties that are similar to biological enzymes to autonomously self-replicate. We test the idea of robotic enzymes using a virtual environment that simulates the currently existing modular robots in a physically accurate way. We describe the self-replicating features of robotic enzymes, and how they could be used to autonomously self-replicate for multiple generations, limited only by the amount of modules in the environment.