Dynamic Control Barrier Function Based Trajectory Planning for Mobile Manipulator

Traditional planning algorithms face challenges in high-dimensional robot trajectory planning. The existing methods encounter numerous issues, such as excessively long computation times, an inability to handle obstacles with high velocities, and occupying much free space. To address these challenges, this paper presents a novel trajectory planning approach that leverages the principles of Dynamic Control Barrier Functions (DCBF) and incorporates geometric computing techniques. The proposed method successfully achieves trajectory planning in environments with dynamic obstacles, ensuring system safety and enabling precise obstacle avoidance. Moreover, the planning algorithm is applied in experiments on a mobile manipulator, demonstrating superior performance.