Study on Collaborative Task Assignment of Sphere Multi-Robot based on Group Intelligence Algorithm

Abstract

With the development of science and technology, many complex problems cannot be completed efficiently by a single robot and require multiple robots to work together. For complex task scenarios with multiple robots, the multi-robot task allocation problem is the key to coordinating robots to work efficiently. In this paper, for the application scenario of multi-robot collaborative inspection task allocation, the task allocation problem is first mathematically modelled using the multi-robot problem model, and simulations based on the resource balance search algorithm and the genetic population intelligence algorithm are applied respectively. Incorporating constraints in the population intelligence genetic algorithm, which transforms robot power constraints into distance constraints for research, allows for targeted simulation solutions for practical multi-robot collaborative detection. The results show that the genetic algorithm based on population intelligence can solve the problem well and minimise the total cost of multi-ball robot clustering, enhance the optimised search capability of the algorithm, improve the rationality of multi-robot task allocation and increase the efficiency of task completion.