A Comparative Study of Artificial Potential Fields and Safety Filters
<|reference_start|>A Comparative Study of Artificial Potential Fields and Safety Filters: In this paper, we have demonstrated that the controllers designed by a classical motion planning tool, namely artificial potential fields (APFs), can be derived from a recently prevalent approach: control barrier function quadratic program (CBF-QP) safety filters. By integrating APF information into the CBF-QP framework, we establish a bridge between these two methodologies. Specifically, this is achieved by employing the attractive potential field as a control Lyapunov function (CLF) to guide the design of the nominal controller, and then the repulsive potential field serves as a reciprocal CBF (RCBF) to define a CBF-QP safety filter. Building on this integration, we extend the design of the CBF-QP safety filter to accommodate a more general class of dynamical models featuring a control-affine structure. This extension yields a special CBF-QP safety filter and a general APF solution suitable for control-affine dynamical models. Through a reach-avoid navigation example, we showcase the efficacy of the developed approaches.<|reference_end|>
@article{li2024a,
    title={A Comparative Study of Artificial Potential Fields and Safety Filters},
    author={Ming Li and Zhiyong Sun},
    journal={arXiv preprint arXiv:2403.15743},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.15743},
    primaryClass={eess.SY cs.AI cs.SY math.DS}
}