This paper presents a reactive planning system that allows a Cassie-series bipedal robot to avoid multiple non-overlapping obstacles via a single, continuously differentiable control barrier function (CBF). The overall system detects an individual obstacle via a height map derived from a LiDAR point cloud and computes an elliptical outer approximation, which is then turned into a CBF. The QP-CLF-CBF formalism developed by Ames et al. is applied to ensure that safe trajectories are generated. Liveness is ensured by an analysis of induced equilibrium points that are distinct from the goal state. Safe planning in environments with multiple obstacles is demonstrated both in simulation and experimentally on the Cassie biped.

翻译：本文介绍了一个反应式规划系统,使Cassi系列双翼机器人能够通过一个单一的、可持续区别的控制屏障功能(CBF)避免多重非重叠障碍。整个系统通过来自LIDAR点云的高度图检测一个个人障碍,并计算出一个外向近似椭圆,然后将其转换为CBF。Ames等人开发的QP-CLF-CBF形式主义用于确保产生安全轨道。通过对与目标状态不同的诱导平衡点的分析,确保了生命安全。在有多重障碍的环境中进行安全规划,在模拟和实验中在Cassie两侧进行。