A flexible active safety motion (FASM) control approach is proposed for the avoidance of dynamic obstacles and the reference tracking in robot manipulators. The distinctive feature of the proposed method lies in its utilization of control barrier functions (CBF) to design flexible CBF-guided safety criteria (CBFSC) with dynamically optimized decay rates, thereby offering flexibility and active safety for robot manipulators in dynamic environments. First, discrete-time CBFs are employed to formulate the novel flexible CBFSC with dynamic decay rates for robot manipulators. Following that, the model predictive control (MPC) philosophy is applied, integrating flexible CBFSC as safety constraints into the receding-horizon optimization problem. Significantly, the decay rates of the designed CBFSC are incorporated as decision variables in the optimization problem, facilitating the dynamic enhancement of flexibility during the obstacle avoidance process. In particular, a novel cost function that integrates a penalty term is designed to dynamically adjust the safety margins of the CBFSC. Finally, experiments are conducted in various scenarios using a Universal Robots 5 (UR5) manipulator to validate the effectiveness of the proposed approach.

翻译：提出了一种柔性主动安全运动（FASM）控制方法，用于机器人操作臂的动态障碍物规避与参考轨迹跟踪。该方法的核心特征在于利用控制障碍函数（CBF）设计具有动态优化衰减率的柔性CBF引导安全准则（CBFSC），从而为动态环境中的机器人操作臂提供柔性与主动安全保障。首先，采用离散时间CBF为机器人操作臂构建具有动态衰减率的新型柔性CBFSC。随后，应用模型预测控制（MPC）原理，将柔性CBFSC作为安全约束集成到滚动时域优化问题中。值得关注的是，所设计的CBFSC衰减率被纳入优化问题的决策变量，从而在障碍规避过程中动态增强柔性。特别地，设计了一种融合惩罚项的新型代价函数，以动态调整CBFSC的安全裕度。最后，使用Universal Robots 5（UR5）操作臂在多种场景下开展实验，验证了所提方法的有效性。