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<p>This paper introduces a unified planning framework for composite hybrid aerial/terrestrial precision manipulators (CHAT-PM), enabling energy-efficient trimodal navigation in complex environments. The proposed path search algorithm leverages terrain-specific heuristics and motion primitives to prioritize energy-saving terrestrial/inclined paths while dynamically selecting optimal motion modes. To address the computational complexity of trimodal dynamics, a unified nonlinear model predictive control (NMPC) approach is developed by integrating complementary constraints, thereby eliminating mixed-integer optimization and unifying aerial-terrestrial-inclined dynamics under a single framework. The dynamics model further incorporates disturbances from robotic arm operations, ground/slope contact forces, and aerodynamic effects, enhancing trajectory accuracy. Finally, the effectiveness and superiority of the proposed method are demonstrated by simulation results and real-world experiments.</p>

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Unified aerial-terrestrial-inclined path search and trajectory optimization for CHAT-PM

  • 期刊论文

  • 发表日期：

    2025年8月22日

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  • Yihang Ding,
  • Lixian Zhang,
  • Ming Liu,
  • Jian Chen,
  • Zainan Jiang

摘要

This paper introduces a unified planning framework for composite hybrid aerial/terrestrial precision manipulators (CHAT-PM), enabling energy-efficient trimodal navigation in complex environments. The proposed path search algorithm leverages terrain-specific heuristics and motion primitives to prioritize energy-saving terrestrial/inclined paths while dynamically selecting optimal motion modes. To address the computational complexity of trimodal dynamics, a unified nonlinear model predictive control (NMPC) approach is developed by integrating complementary constraints, thereby eliminating mixed-integer optimization and unifying aerial-terrestrial-inclined dynamics under a single framework. The dynamics model further incorporates disturbances from robotic arm operations, ground/slope contact forces, and aerodynamic effects, enhancing trajectory accuracy. Finally, the effectiveness and superiority of the proposed method are demonstrated by simulation results and real-world experiments.