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

Khashayar Asadi, Rahul Jain, Ziqian Qin, Mingda Sun, Mojtaba Noghabaei, Jeremy Cole, Kevin Han, Edgar Lobatón

Year
2019
Citations
4

Abstract

The use of camera-equipped robotic platforms for data collection and visually monitoring applications is exponentially growing. Cluttered construction sites with many objects on the ground are challenging environments for a mobile unmanned ground vehicle (UGV) to navigate. 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, 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 frequency of data collection for construction monitoring. 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.

Keywords

Unmanned ground vehicleObstacleArtificial intelligenceRobotic armMobile robotComputer visionComputer scienceObstacle avoidanceStereo cameraRobotics

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