Purpose

This paper aims to propose a one-layer Mamdani hierarchical fuzzy system (HFS) to navigate autonomously an omnidirectional mobile robot to a target with a desired angle in unstructured environment. To avoid collision with unknown obstacles, Mamdani limpid hierarchical fuzzy systems (LHFS) are developed based on infrared sensors information and providing the appropriate linear speed controls.

Design/methodology/approach

The one-layer Mamdani HFS scheme consists of three fuzzy logic units corresponding to each degree of freedom of the holonomic mobile robot. This structure makes it possible to navigate with an optimized number of rules. Mamdani LHFS for obstacle avoidance consists of a number of fuzzy logic units of low dimension connected in a hierarchical structure. Hence, Mamdani LHFS has the advantage of optimizing the number of fuzzy rules compared to a standard fuzzy controller. Based on sensors information inputs of the Mamdani LHFS, appropriate linear speed controls are generated to avoid collision with static obstacles.

Findings

Simulation results are performed with MATLAB software in interaction with the environment test tool “Robotino Sim.” Experiments have been done on an omnidirectional mobile robot “Robotino.” Simulation results show that the proposed approaches lead to satisfied performances in navigation between static obstacles to reach the target with a desired angle and have the advantage that the total number of fuzzy rules is greatly reduced. Experimental results prove the efficiency and the validity of the proposed approaches for the navigation problem and obstacle avoidance collisions.

Originality/value

By comparing simulation results of the proposed Mamdani HFS to another navigational controller, it was found that it provides better results in terms of path length in the same environment. Moreover, it has the advantage that the number of fuzzy rules is greatly reduced compared to a standard Mamdani fuzzy controller. The use of Mamdani LHFS in obstacle avoidance greatly reduces the number of involved fuzzy rules and overcomes the complexity of high dimensionality of the infrared sensors data information.

中文翻译：

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基于层次模糊系统的自主全向移动机器人导航

目的

本文旨在提出一种单层Mamdani层次模糊系统（HFS），以在非结构化环境中将全向移动机器人自主导航到具有所需角度的目标。为了避免与未知障碍物发生碰撞，Mamdani透明层次模糊系统（LHFS）基于红外传感器信息并提供了适当的线性速度控制而开发。

设计/方法/方法

一层的Mamdani HFS方案包含三个模糊逻辑单元，分别对应完整移动机器人的每个自由度。这种结构使得可以使用优化数量的规则进行导航。Mamdani LHFS用于避障，它由多个低维的模糊逻辑单元组成，这些逻辑单元以分层结构连接。因此，与标准模糊控制器相比，Mamdani LHFS具有优化模糊规则数量的优势。根据Mamdani LHFS的传感器信息输入，可以生成适当的线性速度控制，以避免与静态障碍物发生碰撞。

发现

仿真结果是使用MATLAB软件与环境测试工具“ Robotino Sim”交互执行的。已经在全向移动机器人“ Robotino”上进行了实验。仿真结果表明，所提出的方法在静态障碍物之间以期望的角度到达目标的导航性能令人满意，并且具有大大减少模糊规则总数的优点。实验结果证明了所提方法对导航问题和避障碰撞的有效性和有效性。

创意/价值

通过将拟议的Mamdani HFS的仿真结果与另一个导航控制器进行比较，发现在相同环境中，它在路径长度方面提供了更好的结果。此外，与标准的Mamdani模糊控制器相比，它的优点是模糊规则的数量大大减少。Mamdani LHFS在避障中的使用大大减少了所涉及的模糊规则的数量，并克服了红外传感器数据信息的高维复杂性。