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<p>To ensure the feasibility and safety of cable-driven continuum robots (CDCRs) in complex application scenarios with dynamic obstacles and disturbances, a novel cascaded trajectory replanning and tracking controller is proposed. The cascaded controller consists of a kinematic algorithm based on model predictive control (MPC) for trajectory replanning and a dynamic algorithm based on recursive integral terminal sliding mode control (RITSMC) for trajectory tracking. The MPC based trajectory replanning algorithm updates the trajectory of CDCRs to avoid collision with obstacles. The utilization of soft constraint optimization strategy in MPC guarantees the safety of CDCRs during obstacle avoidance, as well as preventing the issue of infeasible solutions that could arise from hard constraints. Furthermore, a super-twisting observer (STO) is integrated into MPC (STO-MPC) to estimate the state of dynamic obstacles and ensure the feasibility of dynamic obstacle avoidance. The RITSMC guarantees fast and accurate trajectory tracking control without imposing significant computational burden compared to MPC. Additionally, an adaptive disturbance observer (ADO) is introduced into RITSMC (ADO-RITSMC) to approximate disturbances and make a compensation, enhancing robustness and accuracy of trajectory tracking control. Experiment cases demonstrate that the cascaded controller exhibits superior performance in trajectory replanning and tracking control for the CDCR with dynamic obstacles and disturbances.</p>

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A cascaded dynamic obstacle avoidance strategy for cable-driven continuum robots based on kinematics and dynamics

  • 期刊论文

  • 发表日期：

    2025年3月12日

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  • Yanan Qin,
  • Qi Chen

摘要

To ensure the feasibility and safety of cable-driven continuum robots (CDCRs) in complex application scenarios with dynamic obstacles and disturbances, a novel cascaded trajectory replanning and tracking controller is proposed. The cascaded controller consists of a kinematic algorithm based on model predictive control (MPC) for trajectory replanning and a dynamic algorithm based on recursive integral terminal sliding mode control (RITSMC) for trajectory tracking. The MPC based trajectory replanning algorithm updates the trajectory of CDCRs to avoid collision with obstacles. The utilization of soft constraint optimization strategy in MPC guarantees the safety of CDCRs during obstacle avoidance, as well as preventing the issue of infeasible solutions that could arise from hard constraints. Furthermore, a super-twisting observer (STO) is integrated into MPC (STO-MPC) to estimate the state of dynamic obstacles and ensure the feasibility of dynamic obstacle avoidance. The RITSMC guarantees fast and accurate trajectory tracking control without imposing significant computational burden compared to MPC. Additionally, an adaptive disturbance observer (ADO) is introduced into RITSMC (ADO-RITSMC) to approximate disturbances and make a compensation, enhancing robustness and accuracy of trajectory tracking control. Experiment cases demonstrate that the cascaded controller exhibits superior performance in trajectory replanning and tracking control for the CDCR with dynamic obstacles and disturbances.