JRM Vol.34 No.3 pp. 607-614
doi: 10.20965/jrm.2022.p0607


Planning the Shortest Carrying Trajectory Including Path and Attitude Change Considering Gripping Constraints

Takahiro Ario and Ikuo Mizuuchi

Tokyo University of Agriculture and Technology
2-24-16 Naka-cho, Koganei-shi, Tokyo 184-8588, Japan

February 25, 2021
January 28, 2022
June 20, 2022
planning, transport, gripper, constraint problem, optimization

Carrying gripped objects at high speed can lead to gripping failure owing to loads applied to the gripper by its acceleration. When carrying an object at high speed, it is important to carry it with accelerations at which gripping is maintained. Previously proposed methods generated the shortest carrying trajectory for a predetermined trajectory path. In this study, focusing on the object-carrying trajectory and the hand attitude of the gripper, we propose a method to generate the shortest carrying trajectory by varying the state quantities. The proposed method considers the gripping force and the deformation of the gripper. During planning, we estimated the deformation volume of the gripper from its inputs and generated the shortest carrying trajectory with the allowable force and deformation values as constraints. Using the proposed method, we generated a trajectory capable of carrying objects in a shorter time (0.28 times) than in a straight-line trajectory and conducted experiments with a robot arm. The trajectory was generated while keeping the hand attitude unchanged. Through experiments, we have proved the effectiveness of keeping objects gripped on the generated shortest carrying trajectory. Compared with a success ratio of 0.47 in keeping objects gripped on the trajectory with the same time as the generated trajectory, the success ratio on the generated trajectory is as high as 1.0.

Short carrying trajectory to prevent grip failure

Short carrying trajectory to prevent grip failure

Cite this article as:
T. Ario and I. Mizuuchi, “Planning the Shortest Carrying Trajectory Including Path and Attitude Change Considering Gripping Constraints,” J. Robot. Mechatron., Vol.34 No.3, pp. 607-614, 2022.
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