# Fault Point Search with Obstacle Avoidance for Machinery Diagnostic Robots Using Hierarchical Fuzzy Logic Control

## TL;DR

This paper introduces a new fuzzy logic-based algorithm for diagnostic robots to navigate and avoid obstacles while reaching fault points in factory environments.

## Contribution

The novel contribution is a hierarchical fuzzy logic control system with dynamic safety boundaries and multi-objective planning for improved robot navigation and obstacle avoidance.

## Key findings

- The algorithm successfully guides diagnostic robots to within 30 cm of fault points.
- Collision avoidance with equipment and obstacles is achieved through dynamic safety boundaries and relative speed analysis.
- Simulation results show enhanced completeness and safety in fault point searching.

## Abstract

Higher requirements have been placed on fault detection for continuously operating machines in modern factories. Manual inspection faces challenges related to timeliness, leading to the emergence of autonomous diagnostic robots. To overcome the safety limitations of existing diagnostic robots in factory environments, a hierarchical fuzzy logic-based navigation and obstacle avoidance algorithm is proposed in this study. The algorithm is constructed based on zero-order Takagi–Sugeno type fuzzy control, comprising subfunctions for navigation, static obstacle avoidance, and dynamic obstacle avoidance. Coordinated navigation and equipment protection are achieved by jointly considering the information of the fault point and surrounding equipment. The concept of a dynamic safety boundary is introduced, wherein the normalized breached level is used to replace the traditional distance-based input. In the inference process for dynamic obstacle avoidance, the relative speed direction is additionally considered. A Mamdani-type fuzzy inference system is employed to infer the necessity of obstacle avoidance and determine the priority target for avoidance, thereby enabling multi-objective planning. Simulation results demonstrate that the proposed algorithm can guide the diagnostic robot to within 30 cm of the fault point while ensuring collision avoidance with both equipment and obstacles, enhancing the completeness and safety of the fault point searching process.