Research On Cooperative Control Problem Of Swarm Robots System

As the scale of multi-robot systems is increasing in recent years, the system control complexity and the communication traffic of multiple robots will exponentially increase, and it is difficult to use traditional algorithms to solve this problem. In nature, there are many social insects---ants, termites, wasps and bees—which can be standed as fascinating examples of how collectively intelligent systems can be generated from a large number of simple individuals. Biologists, computer scientists and roboticists teamed up to transfer their knowledge of social insects behavior to the design of controllers for multi-robot systems. This combined, multidisciplinary effort gave birth to the field of research known as swarm robotics.Campared with the complex single robot and the tranditional multi-robot systems, the characteristics of swarm robotics, such as robustness, scalability, flexiblility and low cost, are better than them. So it will be well researched and widely used in the future. In this thesis, we focused on the cooperative control problem of swarm robotics, and presented some new theories, techniques and algorithms, as follows:1. For consensus problem, we defined the information interactive graph and the information interactive matrix to represent the information interaction relationship and state between each robot based on algebra graph theroy. Proofed the necessary and/or sufficient conditions for consensus and presented some consensus algorithms under static and dynamic topology with error, disturbance, time delay, and input constrains for the first order and the second order sytem, respectively.2. For formation control problem, we analysed the "boids" model using the consensus algorithm for the first order system, and presented two formation control algorithms for the second order system using the virtual force and the flocking theory. Based on the behavior fusion algorithm and the above works, we introduced a flocking formation control algorithm with obstacle avoidance.3. For target searching problem, we introduced a new searching algorithm based on the particle swarm optimization in the enviornment with obstacles. And analysed the influence of information topology of a group of robots for searching task. 4. For swarm controllable problem, we introduced two consensus state tracking algorithms. And invented the "Virtual Entity" technique to sovle the controllable problem for a group of robots based on the wireless sensor network.