Sycamore - 2D/3D Mobile Robots simulation environment

The distributed coordination and control of a team of autonomous mobile robots is a problem widely studied in a variety of fields, such as engineering, artificial intelligence, artificial life, robotics. Generally, in these areas, the problem is studied mostly from a practical point of view. Recently, the study of what can be computed by such team of robots has become increasingly popular in theoretical computer science and especially in distributed computing, where it is now an integral part of the investigations on computability by mobile entities. The autonomous mobile robots model imagines the involved entities being capable of moving, observing the environment and computing. This kind of paradigm often produces complex configurations, for which the mathematical proof of correctness can be found more easily with the help of an empirical approach. This thesis will describe my work on a 2D/3D simulation environment for autonomous mobile robots called Sycamore. The work consisted in the implementation of the simulator and a rich set of plugins for it, followed by the implementation and testing of an algorithm that is solving a problem in the mobile robots theory: "NearGathering". The final part of the work made me design, implement and test a solution for a completely new problem: "Following with directional limited visibility"

Decentralized Control for Swarm Flocking in 3D Space

Second International Conference on Intelligent Robotics and Applications, Singapore, 16-18 December 2009This paper presents a decentralized control strategy for a robot swarm where each robot tries to form a regular tetrahedron with its three neighbors. The proposed method is based on virtual spring. Robots can form regular tetrahedron regardless of their initial positions and they require minimum amount of information about their neighbors. The control strategy is made scalable by integrating a neighbor selection procedure so that it can be expanded to large swarms easily. In addition, an obstacle avoidance mechanism, based on artificial physics, is also introduced. By utilizing this control strategy, basic swarm behaviors such as aggregation, flocking and obstacle avoidance are demonstrated through simulations in an unknown three dimensional environment.Department of Electrical EngineeringRefereed conference pape