Grasp Planning Of Unknown Object For Digital Human Model

作者：Quentin Bourret, P. Lemieux, J. Charland, R. Aissaoui · 发表于：Digital Human Modeling and Applied Optimization · 年份：2022 · DOI：10.54941/ahfe1001908

ObjectiveGrasp planning is a popular topic in the fields of robotic and Digital Human Model (DHM) (4, 6, 7, 9, 10, 11). So far, the proposed planners do not consider the final posture of the DHM has a criteria when determining potential grasps. In (4), a grasping algorithm has been developed to automatically grasp known tools. The present work introduces a grasp planner for single-hand grasp on an unknown object, further referred as “part”.MethodThe grasp planner gives has a result a grasp pose (position + orientation) for the posture solver (Smart Posturing Engine) to reach. The input necessary to the grasp planner are the 3D model of the object to grasp and of the surrounding environment, and an initial manikin position that is automatically determines by the posture solver algorithm.First the part is approximated by its oriented bounding box (OBB), limiting the grasp poses to 6 (one for each face of the OBB). Then precise grasp types (5) and apertures are chosen based on the face’s dimensions (i.e. width and depth), ranging from a small face (i.e. pinch) to larger ones (i.e. medium wrap or precision sphere).To determine what is the best face of the OBB to grasp, accessibility checks are performed by validating that the space around the face is free of collision. The faces are checked using a specific order (i.e. top, right or left, bottom, front, back) that is determined using the relative initial position of the manikin. As soon as a face is found to be graspable and acce...