In the control task of mobile manipulators (MMs), achieving efficient and agile obstacle avoidance in dynamic environments is challenging. In this letter, we present a safe expeditious whole-body (SEWB) control for MMs that ensures both external and internal collision-free. Firstly, control barrier functions (CBFs) are employed for an MM to establish initial safety constraints. Moreover, to resolve the pseudo-equilibrium problem of CBFs and improve avoidance agility, we propose a novel approach called adaptive cyclic inequality (ACI). ACI comprehensively considers obstacles, nominal control to generate directional constraints for MM. Then, we combine CBF and ACI to decompose safety constraints. Considering all these constraints, we formulate a quadratic programming (QP) as our primary optimization. In the QP cost function, we account for the motion accuracy differences between the base and manipulator, as well as obstacle influences, to achieve simultaneous whole-body motion. We validate the effectiveness of our SEWB control in avoiding collision and reaching target points through simulations and real-world experiments, particularly in challenging scenarios that involve fast-moving obstacles. SEWB has been proven to achieve whole-body collision-free and improve avoidance agility.

翻译：在移动机械臂的控制任务中，在动态环境中实现高效、敏捷的避障具有挑战性。本文提出了一种用于移动机械臂的安全快速全身控制方法，该方法能同时确保外部与内部无碰撞。首先，采用控制屏障函数为移动机械臂建立初始安全约束。此外，为解决CBF的伪平衡问题并提升避障敏捷性，我们提出了一种称为自适应循环不等式的新方法。ACI综合考虑障碍物与标称控制，为移动机械臂生成方向性约束。随后，我们将CBF与ACI结合以分解安全约束。综合考虑所有这些约束，我们构建了一个二次规划作为主要优化问题。在QP成本函数中，我们考虑了基座与机械臂之间的运动精度差异以及障碍物影响，以实现同步全身运动。我们通过仿真和真实世界实验验证了所提出的SEWB控制在避免碰撞和抵达目标点方面的有效性，特别是在涉及快速移动障碍物的挑战性场景中。SEWB已被证明能够实现全身无碰撞并提升避障敏捷性。