被动轮式陆空机器人分层规划与模型预测控制

Hierarchical Planning and Model Predictive Control for Passive Wheeled Terrestrial-aerial Bimodal Vehicles

  • 摘要: 针对被动轮式陆空双模态机器人在双模态运动规划与统一控制过程中存在的模态差异、地面非完整约束以及动力学不确定性等问题,本文提出一种规划-控制一体化算法框架。首先,该框架包含一个分层的运动规划器,包括前端的双模态运动学路径搜索算法和后端基于梯度的B样条曲线轨迹优化算法,能在未知环境中生成一条低功耗、安全、平滑且动力学可行的陆空轨迹。此外,该框架还包含一个数据驱动的双模态鲁棒统一控制器与模态切换机制,能够实现精确的轨迹跟踪控制和平稳的模态切换。最后,分别在ROS-Gazebo仿真平台和实物平台进行了算法验证,实验结果证明了所提方法的有效性。

     

    Abstract: To address the issues of modal discrepancies, ground nonholonomic constraints, and dynamic uncertainties encountered in the multimodal motion planning and unified control of passive-wheeled air-ground dual-modal robots, we propose an integrated planning-and-control framework. First, this framework comprises a hierarchical motion planner, including a front-end kinematic path search algorithm and a back-end gradient-based B-spline trajectory optimization algorithm. It generates a low-power, safe, smooth, and dynamically feasible land-air trajectory in unknown environments. It also includes a data-driven robust dual-modal unified controller and mode switching mechanism, enabling precise trajectory tracking control and stable mode switching. Finally, we validate the algorithm in both the ROS-Gazebo simulation platform and a physical platform, demonstrating the effectiveness of our approach.

     

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