Abstract
It is a difficult thing for robot working in a tight and narrow space with obstacles because of collision occurrence. For solving this problem, the paper proposes a joint trajectory generation method for obstacle avoidance. Besides of the end-effector, our work plans a collision free trajectory for each joint in the narrow space. Considering the complexity of obstacle distribution, the presented method combines Dynamic Movement Primitive (DMP) with a RRT-Connect algorithm that firstly, in the joint space DMPs generate trajectories for each manipulator joint, and then, in the cartesian space, the collision detection model checks the DMP generated trajectories. If any of the links collides with the obstacle, a collision free path will be planned on the trajectory points that encounter obstacles by employing RRT-Connect algorithm. Based on ROS platform, the experiments build a tight and narrow simulated environment, and test the method on a UR3 robot manipulator, which show the effectiveness of the presented method.
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Acknowledgment
The work was jointly supported by Beijing Natural Science Foundation (4212933), Scientific Research Project of Beijing Educational Committee (KM202110005023) and National Natural Science Foundation of China (62273012, 62003010).
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Liu, C., Zhang, J., Yu, P., Li, X. (2023). Joint Trajectory Generation of Obstacle Avoidance in Tight Space for Robot Manipulator. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_3
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DOI: https://doi.org/10.1007/978-981-99-0617-8_3
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