Vision-based Obstacle Removal System for Autonomous Ground Vehicles Using a Robotic Arm
This addresses navigation challenges for autonomous ground vehicles in construction environments, but it is incremental as it applies existing vision and robotic arm techniques to a specific domain.
This study tackled the problem of navigating cluttered construction sites by developing a mobile unmanned ground vehicle (UGV) equipped with a stereo camera and robotic arm to detect and remove obstacles, successfully demonstrating obstacle removal in two case studies.
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.