Autonomous trenching robot with intelligent obstacle detection and path optimization for precision cable installation

Abstract

Trenching for underground cable and pipeline installation is typically labor intensive, time-consuming, and potentially hazardous, particularly in environments with buried obstacles. This paper presents a low-cost autonomous trenching robot with intelligent obstacle detection and path optimization to improve excavation efficiency, safety, and accuracy. The proposed system integrates ultrasonic and infrared sensors with an embedded controller for real-time obstacle detection and autonomous navigation. A path optimization algorithm automatically adjusts the trenching route whenever an obstacle is detected, allowing continuous operation while reducing unnecessary movement and energy consumption. The robot employs a tracked mobile platform and an automated trenching mechanism capable of maintaining consistent trench depth and width under different terrain conditions. Experimental results demonstrate that the proposed system accurately detects obstacles, successfully replans its path in real time, and performs reliable autonomous trenching with minimal human intervention. Compared with conventional manual trenching methods, the developed robot improves operational efficiency, enhances excavation accuracy, and reduces safety risks for workers. The proposed system provides a practical and scalable solution for underground cable and pipeline installation and has strong potential for future applications in intelligent construction, infrastructure development, and autonomous civil engineering.