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Active 3D Object Localization Using A Humanoid Robot

By Alexander Andreopoulos, Stephan Hasler, Heiko Wersing, Herbert Janssen, John K. Tsotsos and Edgar Körner


We study the problem of actively searching for an object in a 3D environment under the constraint of a maximum search time, using a visually guided humanoid robot with twentysix degrees of freedom. The inherent intractability of the problem is discussed and a greedy strategy for selecting the best next viewpoint is employed. We describe a target probability updating scheme approximating the optimal solution to the problem, providing an efficient solution to the selection of the best next viewpoint. We employ a hierarchical recognition architecture, inspired by human vision, that uses contextual cues for attending to the view-tuned units at the proper intrinsic scales and for active control of the robotic platform sensor’s coordinate frame, also giving us control of the extrinsic image scale and achieving the proper sequence of pathognomonic views of the scene. The recognition model makes no particular assumptions on shape properties like texture and is trained by showing the object by hand to the robot. Our results demonstrate the feasibility of using state of the art vision-based systems for efficient and reliable object localization in an indoor 3D environment

Topics: Index Terms—Computer Vision, Active Vision, Visual Search, Recognition, Honda’s Humanoid Robot
Year: 2011
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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