Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments
M. Mujahed, D. Fischer, B. Mertsching, Robotics and Autonomous Systems 84 (2016) 15–30.
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Journal Article
| Published
| English
Author
Mujahed, Muhannad;
Fischer, DirkLibreCat 
;
Mertsching, Bärbel
;
Mertsching, BärbelDepartment
Publishing Year
Journal Title
Robotics and Autonomous Systems
Volume
84
Page
15-30
ISSN
LibreCat-ID
Cite this
Mujahed M, Fischer D, Mertsching B. Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments. Robotics and Autonomous Systems. 2016;84:15-30. doi:10.1016/j.robot.2016.07.001
Mujahed, M., Fischer, D., & Mertsching, B. (2016). Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments. Robotics and Autonomous Systems, 84, 15–30. https://doi.org/10.1016/j.robot.2016.07.001
@article{Mujahed_Fischer_Mertsching_2016, title={Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments}, volume={84}, DOI={10.1016/j.robot.2016.07.001}, journal={Robotics and Autonomous Systems}, publisher={Elsevier BV}, author={Mujahed, Muhannad and Fischer, Dirk and Mertsching, Bärbel}, year={2016}, pages={15–30} }
Mujahed, Muhannad, Dirk Fischer, and Bärbel Mertsching. “Tangential Gap Flow (TGF) Navigation: A New Reactive Obstacle Avoidance Approach for Highly Cluttered Environments.” Robotics and Autonomous Systems 84 (2016): 15–30. https://doi.org/10.1016/j.robot.2016.07.001.
M. Mujahed, D. Fischer, and B. Mertsching, “Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments,” Robotics and Autonomous Systems, vol. 84, pp. 15–30, 2016, doi: 10.1016/j.robot.2016.07.001.
Mujahed, Muhannad, et al. “Tangential Gap Flow (TGF) Navigation: A New Reactive Obstacle Avoidance Approach for Highly Cluttered Environments.” Robotics and Autonomous Systems, vol. 84, Elsevier BV, 2016, pp. 15–30, doi:10.1016/j.robot.2016.07.001.
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