Vision-based Obstacle Removal System for Autonomous Ground Vehicles Using a Robotic Arm

TL;DR

This paper introduces a vision-based system combining stereo cameras and a robotic arm on an unmanned ground vehicle to detect and remove obstacles in cluttered construction environments, enhancing autonomous navigation.

Contribution

It presents a novel integrated system for obstacle detection and removal using stereo vision and robotic arm control within a UGV for construction site applications.

Findings

Successful obstacle detection and removal demonstrated in case studies

Enhanced automation and data collection capabilities for construction monitoring

System validation confirms feasibility for autonomous construction vehicle operations

Abstract

Over the past few years, the use of camera-equipped robotic platforms for data collection and visually monitoring applications has exponentially grown. Cluttered construction sites with many objects (e.g., bricks, pipes, etc.) on the ground are challenging environments for a mobile unmanned ground vehicle (UGV) to navigate. To address this issue, this study presents a mobile UGV equipped with a stereo camera and a robotic arm that can remove obstacles along the UGV's path. To achieve this objective, the surrounding environment is captured by the stereo camera and obstacles are detected. The obstacle's relative location to the UGV is sent to the robotic arm module through Robot Operating System (ROS). Then, the robotic arm picks up and removes the obstacle. The proposed method will greatly enhance the degree of automation and the frequency of data collection for construction monitoring. The proposed system is validated through two case studies. The results successfully demonstrate the detection and removal of obstacles, serving as one of the enabling factors for developing an autonomous UGV with various construction operating applications.