Concurrent and Scalable Trajectory Optimization for Manufacturing with Redundant Robots
<|reference_start|>Concurrent and Scalable Trajectory Optimization for Manufacturing with Redundant Robots: We present a concurrent and scalable trajectory optimization method for redundant robots in this paper to improve the quality of robot-assisted manufacturing. The joint angles, the tool orientations and the manufacturing time-sequences are optimized simultaneously on input trajectories with large numbers of waypoints to improve the kinematic smoothness while incorporating the manufacturing constraints. Differently, existing methods always determine them in a decoupled manner. To deal with the large number of waypoints on a toolpath, we propose a decomposition based numerical scheme to optimize the trajectory in an out-of-core manner which can also run in parallel to improve the efficiency. Simulations and physical experiments have been conducted to demonstrate the performance of our method in examples of robot-assisted additive manufacturing.<|reference_end|>
@article{chen2024concurrent,
    title={Concurrent and Scalable Trajectory Optimization for Manufacturing with
  Redundant Robots},
    author={Yongxue Chen, Tianyu Zhang, Yuming Huang, Tao Liu, Charlie C.L. Wang},
    journal={arXiv preprint arXiv:2409.13448},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.13448},
    primaryClass={cs.RO}
}