Online Whole-body Motion Planning for Quadrotor using Multi-resolution Search

TL;DR

This paper introduces a multi-resolution search method for online whole-body motion planning of quadrotors, enabling fast, hierarchical, and successful navigation in unknown environments using onboard sensing.

Contribution

A novel multi-resolution hierarchical planning framework that decomposes the problem into sub-problems, significantly accelerating online quadrotor motion planning in complex environments.

Findings

Planning speed is one to several orders of magnitude faster than existing methods.

High success rate in narrow and unstructured environments.

Effective real-world quadrotor navigation demonstrated.

Abstract

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.