论文标题
使用多分辨率搜索的在线四型四型运动计划
Online Whole-body Motion Planning for Quadrotor using Multi-resolution Search
论文作者
论文摘要
在本文中，我们解决了未知和非结构化环境中在线四型全身运动计划（SE（3）计划）的问题。我们提出了一种新颖的多分辨率搜索方法，该方法发现了需要完整的姿势计划和仅需要位置计划的正常区域的狭窄区域。结果，将四个计划问题分解为几个SE（3）（如有必要）和R^3子问题。为了穿越发现的狭窄区域，提出了一个精心设计的狭窄区域的走廊生成策略，这大大提高了计划的成功率。总体问题分解和分层计划框架大大加速了计划过程，从而可以在未知环境中完全在板载感应和计算上在线工作。广泛的仿真基准比较表明，所提出的方法比计算时间中最先进的方法快几个数量级，同时保持高计划成功率。最终将所提出的方法集成到基于激光雷达的自动脉动四核中，并在未知和非结构化环境中进行了各种现实世界实验，以证明该方法的出色性能。
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 is one to several orders 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.
