To enable safe and efficient use of multi-robot systems in everyday life, a robust and fast method for coordinating their actions must be developed. In this paper, we present a distributed task allocation and scheduling algorithm for missions where the tasks of different robots are tightly coupled with temporal and precedence constraints. The approach is based on representing the problem as a variant of the vehicle routing problem, and the solution is found using a distributed metaheuristic algorithm based on evolutionary computation (CBM-pop). Such an approach allows a fast and near-optimal allocation and can therefore be used for online replanning in case of task changes. Simulation results show that the approach has better computational speed and scalability without loss of optimality compared to the state-of-the-art distributed methods. An application of the planning procedure to a practical use case of a greenhouse maintained by a multi-robot system is given.
翻译:为了在日常生活中安全有效地使用多机器人系统,必须开发一种协调其行动的有力和快速的方法。在本文件中,我们为不同机器人的任务与时间和优先限制紧密结合的飞行任务提出了一个分配任务分配和排期算法。这种方法的基础是将问题作为车辆路由问题的变体来代表,找到解决办法时采用基于进化计算(CBM-pop)的分布的计量经济学算法。这种方法允许快速和接近最佳的分配,因此在任务变化时可用于在线重新规划。模拟结果显示,与最先进的分布方法相比,该方法的计算速度和可调整性更好,不丧失最佳性。在多机器人系统维护的温室的实际使用方面采用了规划程序。