主催: 一般社団法人 日本機械学会
会議名: ロボティクス・メカトロニクス 講演会2022
開催日: 2022/06/01 - 2022/06/04
This paper discusses the development of an environment recognition system in an autonomous overhead traveling crane. In the conventional studies, the trajectory planning methods with load sway suppression and obstacles avoidance have been proposed. The planning methods need the environment recognition with the obstacles location and size in the transport space. Therefore, the environment recognition system which enables to construct automatically the transport prohibited areas in crane transport space is proposed in this paper. In the proposed system, the transport space can be detected by a LiDAR, and the detected data are formed in the grid map. The obstacles are recognized by the morphology transform, the labeling process and k-means. The efficacy of the proposed system is verified by the experiments with the laboratory-type overhead traveling crane.