Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems

@article{Nakka2021ChanceConstrainedTO,
  title={Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems},
  author={Yashwanth Kumar Nakka and Anqi Liu and Guanya Shi and Anima Anandkumar and Yisong Yue and Soon-Jo Chung},
  journal={ArXiv},
  year={2021},
  volume={abs/2005.04374}
}
Learning-based control algorithms require data collection with abundant supervision for training. Safe exploration algorithms ensure the safety of this data collection process even when only partial knowledge is available. We present a new approach for optimal motion planning with safe exploration that integrates chance-constrained stochastic optimal control with dynamics learning and feedback control. We derive an iterative convex optimization algorithm that solves an \underline{Info}rmation… Expand
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