Luxin Han — accepted AI-conference papers

2019

FIESTA: Fast Incremental Euclidean Distance Fields for Online Motion Planning of Aerial Robots

Luxin Han, Fei Gao, Boyu Zhou, Shaojie Shen

IROS 2019poster

Euclidean Signed Distance Field (ESDF) is useful for online motion planning of aerial robots since it can easily query the distance and gradient information against obstacles. Fast incrementally built ESDF map is the bottleneck for conducting real-time motion planning. In this paper, we investigate…

Cited by 241 Source ↗code ↗Scholar ↗

2019

Optimal Trajectory Generation for Quadrotor Teach-and-Repeat

Fei Gao, Luqi Wang, Kaixuan Wang, William Wu, Boyu Zhou, Luxin Han +1

RA-L 2019

In this letter, we propose a novel motion planning framework for quadrotor teach-and-repeat applications. Instead of controlling the drone to precisely follow the teaching path, our method converts an arbitrary jerky human-piloted trajectory to a topologically equivalent one, which is guaranteed to

Cited by 22 Source ↗Scholar ↗