Park, C.-S. Kim, D. 2024-01-20T13:02:26Z 2024-01-20T13:02:26Z 2021-09-02 2013-02 1226-4873 https://pubs.kist.re.kr/handle/201004/128392 To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load. Korean Computational costs Computational loads Humanoid robot Low computational loads Obstacle shapes Real time Unknown environments Walking paths Anthropomorphic robots Computational efficiency Classification of obstacle shape for generating walking path of humanoid robot Article 10.3795/KSME-A.2013.37.2.169 1 Transactions of the Korean Society of Mechanical Engineers, A, v.37, no.2, pp.169 - 176 Transactions of the Korean Society of Mechanical Engineers, A 37 2 169 176 scopus kci ART001740494 2-s2.0-84874844479 Article Computational costs Computational loads Humanoid robot Low computational loads Obstacle shapes Real time Unknown environments Walking paths Anthropomorphic robots Computational efficiency 장애물인식 영역 분할 인간형 로봇 3차원 깊이 지도 Obstacle Detection Range Segmentation Humanoid Robot 3D Depth Map