Group. Mixed Communication Mode Robot Search Problem

Being one of typical swarm intelligent systems, swarm robotics mainly researches how a group of robots with relatively limited ability to complete assigned tasks by swarm intelligence emerged from local interactions. Such artificial systems are characteristic of features of flexibility, robustness and scalability etc. As a mapping relationship between individual robot and particle exists respectively in swarm robotic system for target search and the particle swarm optimization (PSO) algorithm, the standard PSO can be applied to model and coordination control swarm robots after being extended considering their similar working mechanisms. Thus this thesis is focused on studying communication modes in swarm robotic search, and our work are as follows:(1) According to the mapping relationship between swarm robotic search and the standard PSO, we employ the extended particle swarm optimization to model the swarm robots. By applying synchronous and asynchronous communication modes to this problem, we put forward two control algorithms. Then we comparatively analyze the results from simulations conducted in the ideal environment. The results indicate that the asynchronous communication mode predominates over the synchronous both in search efficiency and in energy consumption.(2) As for swarm robotic search taken place in the environment with obstacles, we put forward a mixed communication mode. The robots interact in an asynchronous way when meeting obstacles, and in a synchronous fashion under all other conditions. The results show that the mixed communication mode is more efficient than the synchronous in search efficiency and energy consumption.