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 withcontrollable 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 paper 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：本文针对由无人机（UAV）与无人地面车（UGV）通过可控长度非张紧绳索连接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，这是首个针对非张紧系留有袋类UGV-UAV系统进行轨迹规划的方法。其目标是为有袋类系统的三个要素（UAV、UGV及系留绳索）确定同步的无碰撞轨迹。首先，我们提出一种基于最优快速随机扩展树（RRT*）的路径规划方案，该方案采用新颖的采样与导向技术以加速计算。该算法能够考虑三维环境与系留绳索，为UAV和UGV生成无碰撞路径。随后，本文提出一种基于非线性最小二乘的轨迹规划器。该优化器考虑了路径规划中未涉及的方面，如受机器人速度与加速度限制的运动时间约束，以及提升系留绳索离地间隙等要求。仿真与实地测试结果表明，该方法可为有袋类系统生成无碰撞、平滑且可行的轨迹。