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Cited by 349

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Camera-based navigation of a low-cost quadrocopter

Engel, Jakob, Sturm, Jurgen, Cremers, Daniel·2012·2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

Abstract

In this paper, we describe a system that enables a low-cost quadrocopter coupled with a ground-based laptop to navigate autonomously in previously unknown and GPS-denied environments. Our system consists of three components: a monocular SLAM system, an extended Kalman filter for data fusion and state estimation and a PID controller to generate steering commands. Next to a working system, the main contribution of this paper is a novel, closed-form solution to estimate the absolute scale of the generated visual map from inertial and altitude measurements. In an extensive set of experiments, we demonstrate that our system is able to navigate in previously unknown environments at absolute scale without requiring artificial markers or external sensors. Furthermore, we show (1) its robustness to temporary loss of visual tracking and significant delays in the communication process, (2) the elimination of odometry drift as a result of the visual SLAM system and (3) accurate, scale-aware pose estimation and navigation.

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Metadata

Authors
Engel, J., Sturm, J., & Cremers, D.
Venue
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
IEEE
Published
2012-10
Pages
2815-2821
OpenAlex
W1975713381
Cited by
349
References
19
FWCI
69.30
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Camera-based navigation of a low-cost quadrocopter. https://app.cochat.ai/papers/10.1109/iros.2012.6385458
The paper
Engel, J., Sturm, J., & Cremers, D. (2012). Camera-based navigation of a low-cost quadrocopter. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/iros.2012.6385458

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.