This paper introduces CBFKit, a Python/ROS toolbox for safe robotics planning and control under uncertainty. The toolbox provides a general framework for designing control barrier functions for mobility systems within both deterministic and stochastic environments. It can be connected to the ROS open-source robotics middleware, allowing for the setup of multi-robot applications, encoding of environments and maps, and integrations with predictive motion planning algorithms. Additionally, it offers multiple CBF variations and algorithms for robot control. The CBFKit is demonstrated on the Toyota Human Support Robot (HSR) in both simulation and in physical experiments.

翻译：本文介绍CBFKit——一个用于不确定环境下安全机器人规划与控制的Python/ROS工具箱。该工具箱为确定性及随机环境下的移动系统提供了通用化控制障碍函数设计框架。其可对接ROS开源机器人中间件，支持多机器人应用配置、环境与地图编码，以及与预测运动规划算法的集成。此外，工具箱还提供多种CBF变体及机器人控制算法。CBFKit已在丰田人类支援机器人（HSR）上通过仿真与物理实验完成验证。