In this paper, we address the problem of online quadrotor whole-body motion planning (SE(3) planning) in unknown and unstructured environments. We propose a novel multi-resolution search method, which discovers narrow areas requiring full pose planning and normal areas requiring only position planning. As a consequence, a quadrotor planning problem is decomposed into several SE(3) (if necessary) and R^3 sub-problems. To fly through the discovered narrow areas, a carefully designed corridor generation strategy for narrow areas is proposed, which significantly increases the planning success rate. The overall problem decomposition and hierarchical planning framework substantially accelerate the planning process, making it possible to work online with fully onboard sensing and computation in unknown environments. Extensive simulation benchmark comparisons show that the proposed method has an order of magnitude faster than the state-of-the-art methods in computation time while maintaining high planning success rate. The proposed method is finally integrated into a LiDAR-based autonomous quadrotor, and various real-world experiments in unknown and unstructured environments are conducted to demonstrate the outstanding performance of the proposed method.
翻译:在本文中,我们讨论了在未知和无结构环境中的在线四甲酸四甲酯全体运动规划(SE(3)规划)问题;我们建议采用新的多分辨率搜索方法,发现需要全方位规划和仅需要定位规划的正常区域的狭窄区域;因此,四甲酸四甲酯规划问题被分解成若干个SE(3)(如有必要)和R ⁇ 3次问题;为了在所发现的狭窄区域飞行,提出了精心设计的窄区域走廊生成战略,这大大提高了规划成功率;总体问题分解和等级规划框架大大加快了规划过程,使得有可能在未知环境中完全在船上进行感测和计算;广泛的模拟基准比较表明,拟议的方法在计算时间比目前采用的方法规模要快,同时保持较高的规划成功率;拟议的方法最终被纳入了以LIDAR为基础的自主四甲酸酯自治的四甲酸酯,并在未知和未结构化的环境中进行了各种实际世界实验,以展示拟议方法的杰出表现。