论文标题
更快：在未知环境中导航的快速安全轨迹规划师
FASTER: Fast and Safe Trajectory Planner for Navigation in Unknown Environments
论文作者
论文摘要
在未知环境中规划无人机的高速轨迹需要算法技术，使快速反应时间可以确保安全性，因为有关环境的更多信息可用。通过在自由广告空间中执行“停止”条件来确保安全的标准方法可以严重限制车辆的速度，尤其是在世界上许多未知的情况下。此外，通常对轨迹施加的临时时间和间隔分配方案也导致保守和较慢的轨迹。这项工作提出了更快（快速安全的轨迹计划者），以确保安全而不会牺牲速度。通过使本地规划师能够在自由空间和未知空间中进行优化，可以更快地获得高速轨迹。通过在自由空间中始终具有安全的备份轨迹来确保安全。提出的MIQP公式还允许求解器选择轨迹间隔分配。更快的速度在模拟和实际硬件中进行了广泛的测试，显示了速度高达7.8m/s的未知杂物环境中的飞行，并且以踢脚式接地机器人（2m/s）的最大速度进行实验。
Planning high-speed trajectories for UAVs in unknown environments requires algorithmic techniques that enable fast reaction times to guarantee safety as more information about the environment becomes available. The standard approaches that ensure safety by enforcing a "stop" condition in the free-known space can severely limit the speed of the vehicle, especially in situations where much of the world is unknown. Moreover, the ad-hoc time and interval allocation scheme usually imposed on the trajectory also leads to conservative and slower trajectories. This work proposes FASTER (Fast and Safe Trajectory Planner) to ensure safety without sacrificing speed. FASTER obtains high-speed trajectories by enabling the local planner to optimize in both the free-known and unknown spaces. Safety is ensured by always having a safe back-up trajectory in the free-known space. The MIQP formulation proposed also allows the solver to choose the trajectory interval allocation. FASTER is tested extensively in simulation and in real hardware, showing flights in unknown cluttered environments with velocities up to 7.8m/s, and experiments at the maximum speed of a skid-steer ground robot (2m/s).
