Baldassarre Gianluca, Trianni Vito, Bonani Michael, Mondada Francesco, Dorigo Marco, Nolfi Stefano
Laboratory of Autonomous Robotics and Artificial Life, Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche, 00185 Rome, Italy.
IEEE Trans Syst Man Cybern B Cybern. 2007 Feb;37(1):224-39. doi: 10.1109/tsmcb.2006.881299.
An important goal of collective robotics is the design of control systems that allow groups of robots to accomplish common tasks by coordinating without a centralized control. In this paper, we study how a group of physically assembled robots can display coherent behavior on the basis of a simple neural controller that has access only to local sensory information. This controller is synthesized through artificial evolution in a simulated environment in order to let the robots display coordinated-motion behaviors. The evolved controller proves to be robust enough to allow a smooth transfer from simulated to real robots. Additionally, it generalizes to new experimental conditions, such as different sizes/shapes of the group and/or different connection mechanisms. In all these conditions the performance of the neural controller in real robots is comparable to the one obtained in simulation.
群体机器人技术的一个重要目标是设计控制系统,使机器人群体能够在无需集中控制的情况下通过协作完成共同任务。在本文中,我们研究了一组物理组装的机器人如何基于一个仅能获取局部感官信息的简单神经控制器来展现连贯行为。该控制器通过在模拟环境中的人工进化进行合成,以使机器人展现协调运动行为。事实证明,进化后的控制器足够强大,能够实现从模拟机器人到真实机器人的平稳过渡。此外,它还能推广到新的实验条件,如群体的不同尺寸/形状和/或不同的连接机制。在所有这些条件下,神经控制器在真实机器人中的性能与在模拟中获得的性能相当。