Abstract The collision-free navigation of a mobile robot in clutter environments is challenging. Global Positioning System (GPS) and adaptive neuro-fuzzy inference system (ANFIS) are well-known techniques widely used for navigation and control, respectively. This paper proposes a hybrid GPS-ANFIS based method for collision-free navigation of autonomous mobile robots. The GPS-based controller keeps the navigation direction of the robot toward the static or dynamic target. It uses the coordinates received from the two GPS modules on the edges of the longitudinal axis of the robot all together with the coordinates of the target to divert it from the current path making a certain angle towards the target. The performance of the proposed method in navigating a mobile robot in clutter environments and its effectiveness in comparison with the other collision-free navigation methods has been evaluated through simulations. The evaluation criteria are on the basis of the obstacle avoidance behavior and the length of the discovered collision-free path by the robot. The results have shown that our hybrid GPS-ANFIS method navigates the robot toward the goal via a shorter path while avoiding the obstacles.

中文翻译：

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基于混合全球定位系统-自适应神经模糊推理系统的自主移动机器人导航

摘要 移动机器人在杂乱环境中的无碰撞导航具有挑战性。全球定位系统 (GPS) 和自适应神经模糊推理系统 (ANFIS) 分别是广泛用于导航和控制的众所周知的技术。本文提出了一种基于混合 GPS-ANFIS 的自主移动机器人无碰撞导航方法。基于 GPS 的控制器保持机器人朝向静态或动态目标的导航方向。它使用从机器人纵轴边缘上的两个 GPS 模块接收到的坐标以及目标的坐标，将其从当前路径转移到目标的某个角度。通过仿真评估了所提出的方法在杂波环境中导航移动机器人的性能及其与其他无碰撞导航方法相比的有效性。评估标准基于机器人的避障行为和发现的无碰撞路径的长度。结果表明，我们的混合 GPS-ANFIS 方法在避开障碍物的同时，通过更短的路径将机器人导航到目标。