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pro vyhledávání: '"Damron, Hunter"'
This paper addresses the robustness problem of visual-inertial state estimation for underwater operations. Underwater robots operating in a challenging environment are required to know their pose at all times. All vision-based localization schemes ar
Externí odkaz:
http://arxiv.org/abs/2304.01988
Autor:
Joshi, Bharat, Modasshir, Md, Manderson, Travis, Damron, Hunter, Xanthidis, Marios, Li, Alberto Quattrini, Rekleitis, Ioannis, Dudek, Gregory
In this paper, we propose a real-time deep learning approach for determining the 6D relative pose of Autonomous Underwater Vehicles (AUV) from a single image. A team of autonomous robots localizing themselves in a communication-constrained underwater
Externí odkaz:
http://arxiv.org/abs/2003.05523
Autor:
Xanthidis, Marios, Karapetyan, Nare, Damron, Hunter, Rahman, Sharmin, Johnson, James, O'Connell, Allison, O'Kane, Jason M., Rekleitis, Ioannis
Navigation underwater traditionally is done by keeping a safe distance from obstacles, resulting in "fly-overs" of the area of interest. Movement of an autonomous underwater vehicle (AUV) through a cluttered space, such as a shipwreck or a decorated
Externí odkaz:
http://arxiv.org/abs/1903.11750
Bearing only cooperative localization has been used successfully on aerial and ground vehicles. In this paper we present an extension of the approach to the underwater domain. The focus is on adapting the technique to handle the challenging visibilit
Externí odkaz:
http://arxiv.org/abs/1809.03594