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Search-based 3D Planning and Trajectory Optimization for Safe Micro Aerial Vehicle Flight Under Sensor Visibility Constraints

机译:传感器可见性约束下基于搜索的3D规划和轨迹优化,用于安全的微型飞行器飞行

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Safe navigation of Micro Aerial Vehicles (MAVs) requires not only obstacle-free flight paths according to a static environment map, but also the perception of and reaction to previously unknown and dynamic objects. This implies that the onboard sensors cover the current flight direction. Due to the limited payload of MAVs, full sensor coverage of the environment has to be traded off with flight time. Thus, often only a part of the environment is covered. We present a combined allocentric complete planning and trajectory optimization approach taking these sensor visibility constraints into account. The optimized trajectories yield flight paths within the apex angle of a Velodyne Puck Lite 3D laser scanner enabling low-level collision avoidance to perceive obstacles in the flight direction. Furthermore, the optimized trajectories take the flight dynamics into account and contain the velocities and accelerations along the path. We evaluate our approach with a DJI Matrice 600 MAV and in simulation employing hardware-in-the-loop.
机译:微型飞行器(MAV)的安全导航不仅需要根据静态环境图的无障碍飞行路径,而且还需要感知和响应先前未知的动态物体。这意味着机载传感器覆盖了当前的飞行方向。由于MAV的有效载荷有限,因此必须权衡整个环境的传感器覆盖范围和飞行时间。因此,通常仅覆盖一部分环境。考虑到这些传感器可见性的约束,我们提出了一种组合的全中心完整的计划和轨迹优化方法。优化的轨迹可在Velodyne Puck Lite 3D激光扫描仪的顶角范围内产生飞行路径,从而能够避免低水平碰撞,从而感知飞行方向上的障碍物。此外,优化的轨迹将飞行动力学考虑在内,并包含沿路径的速度和加速度。我们使用DJI Matrice 600 MAV评估了我们的方法,并在仿真中使用了硬件在环系统。

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