In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast maneuvers) do not allow to constantly maintain the line of sight with a target of interest. Instead, we compute the optimal trajectory by solving a non-linear optimization problem that minimizes the target re-projection error while meeting the UAV's dynamic constraints. The desired trajectory is then tracked by means of a real-time Non-linear Model Predictive Controller (NMPC): this implicitly allows the multirotor to satisfy both the required constraints. We successfully evaluate the proposed approach in many real and simulated experiments, making an exhaustive comparison with a standard approach.
@article{arxiv.1705.10960,
title = {Effective Target Aware Visual Navigation for UAVs},
author = {Ciro Potena and Daniele Nardi and Alberto Pretto},
journal= {arXiv preprint arXiv:1705.10960},
year = {2018}
}
Comments
Conference paper at "European Conference on Mobile Robotics" (ECMR) 2017