Vision-encoder-based Payload State Estimation for Autonomous MAV With a Suspended Payload
Yunfan Ren, Jianheng Liu, Haoyao Chen, Yunhui Liu
Abstract
Autonomous delivery of suspended payloads with MAVs has many applications in rescue and logistics transportation. Robust and online estimation of the payload status is important but challenging especially in outdoor environments. The paper develops a novel real-time system for estimating the payload position; the system consists of a monocular fisheye camera and a novel encoder-based device. A Gaussian fusion-based estimation algorithm is developed to obtain the payload state estimation. Based on the robust payload position estimation, a payload controller is presented to ensure the re-liable tracking performance on aggressive trajectories. Several experiments are performed to validate the high performance of the proposed method.
BibTeX
@inproceedings{iros2021_visionencoderbas,
title = {Vision-encoder-based Payload State Estimation for Autonomous MAV With a Suspended Payload},
author = {Yunfan Ren and Jianheng Liu and Haoyao Chen and Yunhui Liu},
booktitle = {IROS 2021},
year = {2021}
}