In the multi-robot system, how to achieve effective and reasonable task coordination between multi-robots is an important problem;, multi-robot task scheduling is the term used for the coordination of the key technologies. Therefore, in this paper we combined the pilot scheduling method with the following method and the behavior method of the robot based on task scheduling, and we then studied how to improve the traditional robot scheduling effect, which is a deep-learning algorithm that is applied to multi-robot scheduling to formulate an action selection strategy. We thus proved the effectiveness of this idea experimentally. Based on the above research foundation, this paper continues to build a simple simulation experiment platform, which simply sets up three obstacles and completes the task of robot scheduling on the platform.

中文翻译：

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基于机器视觉的多机器人调度算法研究

在多机器人系统中，如何实现多机器人之间有效，合理的任务协调是一个重要的问题；多机器人任务调度是关键技术协调的术语。因此，本文将飞行员调度方法与以下方法和基于任务调度的机器人行为方法相结合，然后研究如何提高传统的机器人调度效果，这是一种适用于深度学习的算法多机器人调度来制定动作选择策略。因此，我们通过实验证明了该想法的有效性。在上述研究基础上，本文继续构建一个简单的仿真实验平台，该平台简单设置了三个障碍，并完成了平台上机器人调度的任务。