LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments

@article{Shirai2021LTOLT,
  title={LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments},
  author={Yuki Shirai and Xuan Lin and Ankur M. Mehta and Dennis W. Hong},
  journal={2021 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2021},
  pages={7533-7539}
}
  • Y. Shirai, Xuan Lin, D. Hong
  • Published 1 March 2021
  • Computer Science
  • 2021 IEEE International Conference on Robotics and Automation (ICRA)
Although Trajectory Optimization (TO) is one of the most powerful motion planning tools, it suffers from expensive computational complexity as a time horizon increases in cluttered environments. It can also fail to converge to a globally optimal solution. In this paper, we present Lazy Trajectory Optimization (LTO) that unifies local short-horizon TO and global Graph-Search Planning (GSP) to generate a long-horizon global optimal trajectory. LTO solves TO with the same constraints as the… 

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