Observer-Based Environment Robust Control Barrier Functions for Safety-critical Control with Dynamic Obstacles
<|reference_start|>Observer-Based Environment Robust Control Barrier Functions for Safety-critical Control with Dynamic Obstacles: This paper proposes a safety-critical controller for dynamic and uncertain environments, leveraging a robust environment control barrier function (ECBF) to enhance the robustness against the measurement and prediction uncertainties associated with moving obstacles. The approach reduces conservatism, compared with a worst-case uncertainty approach, by incorporating a state observer for obstacles into the ECBF design. The controller, which guarantees safety, is achieved through solving a quadratic programming problem. The proposed method's effectiveness is demonstrated via a dynamic obstacle-avoidance problem for an autonomous vehicle, including comparisons with established baseline approaches.<|reference_end|>
@article{quan2024observer-based,
    title={Observer-Based Environment Robust Control Barrier Functions for
  Safety-critical Control with Dynamic Obstacles},
    author={Ying Shuai Quan, Jian Zhou, Erik Frisk, Chung Choo Chung},
    journal={arXiv preprint arXiv:2403.13288},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.13288},
    primaryClass={eess.SY cs.SY}
}