This article proposes a new multistage evolutionary fuzzy control configuration and navigation of three-wheeled robots cooperatively carrying an overhead object in unknown environments. Based on the divide-and-conquer technique, this article proposes a stage-by-stage evolutionary obstacle boundary following (OBF) fuzzy control of each of the three robots through multiobjective continuous ant colony optimization. In the first stage, a set of evolutionary nondominated fuzzy controllers (FCs) for a single robot (a leader robot) in the execution of the OBF behavior is learned. In the second stage, a follower robot is controlled by two evolutionary FCs in combination with a switched compensation FC so that the leader and follower robots can cooperatively transport an object while executing the OBF behavior along obstacles containing corners with right angles. In the third stage, the third robot functions as an accompanying robot and is learned to enter into a predicted triangular formation with the leader_follower robots to transport a larger object while executing the OBF behavior. In the navigation of the three object-transportation robots, a new cooperative behavior supervisor is proposed to coordinate the learned OBF behavior and a target seeking behavior. Successful navigations in simulations and experiments verify the effectiveness of the multistage evolutionary fuzzy control approach and navigation scheme.

中文翻译：

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使用多级进化模糊控制方法的三个协作物体运输机器人的导航


本文提出了一种新的多级进化模糊控制配置和三轮机器人在未知环境中协作搬运头顶物体的导航。基于分而治之技术，本文通过多目标连续蚁群优化，提出了对三个机器人进行分阶段进化障碍边界跟随（OBF）模糊控制。在第一阶段，学习一组用于单个机器人（领导机器人）执行 OBF 行为的进化非支配模糊控制器（FC）。在第二阶段，跟随机器人由两个进化 FC 与切换补偿 FC 相结合控制，以便引导机器人和跟随机器人可以协作运输物体，同时沿着包含直角拐角的障碍物执行 OBF 行为。在第三阶段，第三个机器人充当伴随机器人，并学会与leader_follower机器人进入预测的三角形队形，以在执行OBF行为时运输较大的物体。在三个物体运输机器人的导航中，提出了一种新的协作行为监督器来协调学习的 OBF 行为和目标搜索行为。仿真和实验中的成功导航验证了多级进化模糊控制方法和导航方案的有效性。