Experiment Design for Stochastic Three-Dimensional Reconfiguration of Modular Robots

Two important trends of modern modular robotics research are module size reduction and the increase of the total number of modules in a robotic system. Smaller and simpler modules are expected to be cheaper if fabricated in bulk and easier to selectively replace in a modular system in case of failures. Stochastic methods of modular robots assembly and reconfiguration enable individual module simplification and miniaturization because modules can be constructed without on-board power supplies, locomotion controllers, or actuators [1, 2]. However, stochastic reconfiguration is in many respects dependent upon the properties and operation of the environment where the modules reconfigure [3-5]. This paper discusses the challenges in design and control of the artificial environment constructed for experiments in threedimensional stochastic reconfiguration of modular robots.