Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors-Reference-Cited by-同舟云学术

Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors

Published:2013-06 Issue:9 Volume:27 Page:711-724
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Müller Jörg,Burgard Wolfram

Publisher

Informa UK Limited

Subject

Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering

Link

http://www.tandfonline.com/doi/pdf/10.1080/01691864.2013.779005

Reference42 articles.

1. Müller J, Rottmann A, Burgard W. A Probabilistic sonar sensor model for robust localization of a small-size blimp in indoor environments using a particle filter. In: Proceedings of the IEEE International Conference on Robotics & Automation (ICRA); 2009; Kobe, Japan. p. 3589–3594.

2. Müller J, Gonsior C, Burgard W. Improved monte carlo localization of autonomous robots through simultaneous estimation of motion model parameters. In: Proceedings of the IEEE International Conference on Robotics & Automation (ICRA); 2010; Anchorage, AK, USA. p. 2604–2609.

3. Gomes SBV, Ramos JG Jr. Airship dynamic modeling for autonomous operation. In: Proceedings of the IEEE International Conference on Robotics & Automation (ICRA); 1998; Leuven, Belgium. p. 3462–3467.

4. Ko J, Klein DJ, Fox D, Haehnel D. GP-UKF: unscented kalman filters with gaussian process prediction and observation models. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2007; San Diego, CA, USA. p. 1901–1907.

5. Flying over the reality gap: From simulated to real indoor airships

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