This letter addresses the problem of trajectory planning in a marsupial robotic system consisting of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) through a non-taut tether with controllable length. To the best of our knowledge, this is the first method that addresses the trajectory planning of a marsupial UGV-UAV with a non-taut tether. The objective is to determine a synchronized collision-free trajectory for the three marsupial system agents: UAV, UGV, and tether. First, we present a path planning solution based on optimal Rapidly-exploring Random Trees (RRT*) with novel sampling and steering techniques to speed-up the computation. This algorithm is able to obtain collision-free paths for the UAV and the UGV, taking into account the 3D environment and the tether. Then, the letter presents a trajectory planner based on non-linear least squares. The optimizer takes into account aspects not considered in the path planning, like temporal constraints of the motion imposed by limits on the velocities and accelerations of the robots, or raising the tether's clearance. Simulated and field test results demonstrate that the approach generates obstacle-free, smooth, and feasible trajectories for the marsupial system.

翻译：本文针对由无人飞行器（UAV）与无人地面车辆（UGV）通过可控长度非拉紧系绳连接组成的有袋类机器人系统中的轨迹规划问题展开研究。据我们所知，这是首个处理非拉紧系绳连接的有袋类UGV-UAV系统轨迹规划的方法。其目标是为有袋类系统三个智能体（UAV、UGV及系绳）确定同步无碰撞轨迹。首先，我们提出基于最优快速扩展随机树（RRT*）的路径规划方案，通过新颖的采样和导向技术加速计算。该算法能够考虑三维环境与系绳因素，获取UAV与UGV的无碰撞路径。继而，本文提出基于非线性最小二乘法的轨迹规划器。该优化器考虑了路径规划中未涉及的因素，如机器人速度与加速度约束所施加的时间运动限制，以及提升系绳净空高度等。仿真与实地测试结果表明，该方法能为有袋类系统生成无障碍、平滑且可行的轨迹。