P-CAP: Pre-Computed Alternative Paths to Enable Aggressive Aerial Maneuvers in Cluttered Environments
P-CAP: Pre-Computed Alternative Paths to Enable Aggressive Aerial Maneuvers in Cluttered Environments
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P-CAP：预先计算的替代路径，可在杂乱的环境中实现积极的空中机动
DOI：
10.1109/iros.2018.8593826
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Sanjiv Singh
中科院分区：
文献类型：
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作者：
Ji Zhang;Rushat Gupta Chadha;Vivek Velivela;Sanjiv Singh
我们提出了一种新的方法来实现在混乱环境下的快速自主飞行。通常，通过复杂环境的自主导航需要对由k连接网格或概率方案生成的图进行连续的启发式搜索。随着车辆的发展，使用车载传感器的数据来修改图是昂贵的，在图上搜索也是昂贵的，特别是当路径必须是kino-动态可行的时候。我们建议，如果我们在飞行前预先计算并仔细安排一组密集的备选路径，可以大大减少在快速飞行中寻找安全路径所需的计算。任何先前的地图信息都可以用来修剪替代路径，从而形成一个数据结构，使快速在线计算能够处理地图上没有的障碍物，而这些障碍物只有车载传感器才能检测到。为了验证这个想法，我们在结构化（大型工业设施）和非结构化（类似森林）环境中进行了大量的飞行实验。我们证明，即使在最非结构化的环境中，这种方法也能以高达10米/秒的速度飞行，同时避开机载传感器检测到的障碍物。
We propose a novel method to enable fast autonomous flight in cluttered environments. Typically, autonomous navigation through a complex environment requires a continuous heuristic search on a graph generated by a k-connected grid or a probabilistic scheme. As the vehicle progresses, modification of the graph with data from onboard sensors is expensive as is search on the graph, especially if the paths must be kino-dynamically feasible. We suggest that computation needed to find safe paths during fast flight can be greatly reduced if we precompute and carefully arrange a dense set of alternative paths before the flight. Any prior map information can be used to prune the alternative paths to come up with a data structure that enables very fast online computation to deal with obstacles that are not on the map but only detected by onboard sensors. To test this idea, we have conducted a large number of flight experiments in structured (large industrial facilities) and unstructured (forests-like) environments. We show that even in the most unstructured environments, this method enables flight at a speed up to 10m/s while avoiding obstacles detected from onboard sensors.