In this paper, we propose a safety-critical controller based on time-varying control barrier functions (CBFs) for a robot with an unicycle model in the continuous-time domain to achieve navigation and dynamic collision avoidance. Unlike previous works, our proposed approach can control both linear and angular velocity to avoid collision with obstacles, overcoming the limitation of confined control performance due to the lack of control variable. To ensure that the robot reaches its destination, we also design a control Lyapunov function (CLF). Our safety-critical controller is formulated as a quadratic program (QP) optimization problem that incorporates CLF and CBFs as constraints, enabling real-time application for navigation and dynamic collision avoidance. Numerical simulations are conducted to verify the effectiveness of our proposed approach.

翻译：本文提出了一种基于时变控制障碍函数的连续时间域单轮模型机器人安全关键控制器，以实现导航与动态避障。与现有研究不同，本方法能够同时控制线速度和角速度以避免与障碍物碰撞，克服了因控制变量缺失导致的控制性能受限问题。为确保机器人到达目标位置，我们还设计了控制李雅普诺夫函数。安全关键控制器被构造成带有控制李雅普诺夫函数和时变控制障碍函数约束的二次规划（QP）优化问题，从而支持导航与动态避障的实时应用。通过数值仿真验证了所提方法的有效性。