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Mesh Manifold Based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles | IEEE Journals & Magazine | IEEE Xplore

Mesh Manifold Based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles

Publisher: IEEE

Abstract:

This letter presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a solution to the problem of finding trajectori...View more

Abstract:

This letter presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a solution to the problem of finding trajectories that drive a robot towards a surface and move along it. Triangular meshes are used as a surface map representation that is free of fixed discretization and allows for very large workspaces. We propose to leverage planar parametrization methods to obtain a lower-dimensional topologically equivalent representation of the original surface. Furthermore, we interpret the original surface and its lower-dimensional representation as manifold approximations that allow the use of Riemannian Motion Policies (RMPs), resulting in an efficient, versatile, and elegant motion generation framework. We compare against several Rapidly-exploring Random Tree (RRT) planners, a customized CHOMP variant, and the discrete geodesic algorithm. Using extensive simulations on real-world data we show that the proposed planner can reliably plan high-quality near-optimal trajectories at minimal computational cost. The accompanying multimedia attachment demonstrates feasibility on a real OMAV. The obtained paths show less than 10 \% deviation from the theoretical optimum while facilitating reactive re-planning at kHz refresh rates, enabling flying robots to perform motion planning for interaction with complex surfaces.
Published in: IEEE Robotics and Automation Letters ( Volume: 6, Issue: 3, July 2021)
Page(s): 4790 - 4797
Date of Publication: 24 February 2021

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Publisher: IEEE

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