Efficient Trajectory Library Filtering for Quadrotor Flight in Unknown Environments

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“Efficient Trajectory Library Filtering for Quadrotor Flight in Unknown Environments” by V.K. Viswanathan, E. Dexheimer, G. Li, G. Loianno, M. Kaess, and S. Scherer. In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 2510-2517.

Abstract

Quadrotor flight in unknown environments is challenging due to the limited range of perception sensors, state estimation drift, and limited onboard computation. In this work, we tackle these challenges by proposing an efficient, reactive planning approach. We introduce the Bitwise Trajectory Eliminiation (BiTE) algorithm for efficiently filtering out in-collision trajectories from a trajectory library by using bitwise operations. Then, we outline a full planning approach for quadrotor flight in unknown environments. This approach is evaluated extensively in simulation and shown to require up to 90% less computation than comparable approaches. Finally, we validate our planner in over 120 minutes of flights in forest-like and urban subterranean environments.

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BibTeX entry:

@inproceedings{Viswanathan20iros,
   author = {V.K. Viswanathan and E. Dexheimer and G. Li and G. Loianno
	and M. Kaess and S. Scherer},
   title = {Efficient Trajectory Library Filtering for Quadrotor Flight in
	Unknown Environments},
   booktitle = {Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and
	Systems, IROS},
   pages = {2510-2517},
   month = oct,
   year = {2020}
}
Last updated: November 10, 2024