Active 3D Object Localization Using a Humanoid Robot
Alexander Andreopoulos,Stephan Hasler,Heiko Wersing,Herbert Janssen,John K. Tsotsos,Edgar Körner +5 more
TLDR
A target probability updating scheme is described, providing an efficient solution to the selection of the best next viewpoint in the problem of actively searching for an object in a 3-D environment under the constraint of a maximum search time using a visually guided humanoid robot with 26 degrees of freedom.Abstract:
We study the problem of actively searching for an object in a three-dimensional (3-D) environment under the constraint of a maximum search time using a visually guided humanoid robot with 26 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, which also gives us control of the extrinsic image scale and achieves 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 3-D environment.read more
Citations
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Journal ArticleDOI
50 Years of object recognition: Directions forward☆
TL;DR: It is argued that the next step in the evolution of object recognition algorithms will require radical and bold steps forward in terms of the object representations, as well as the learning and inference algorithms used.
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Revisiting active perception.
TL;DR: In this article, the authors present a history of active perception in robotics, artificial intelligence and computer vision, highlighting the seminal contributions and argue that those contributions are as relevant today as they were decades ago and, with the state of modern computational tools, are poised to find new life in robotic perception systems of the next decade.
Posted Content
Revisiting Active Perception
TL;DR: It is argued that those contributions are as relevant today as they were decades ago and, with the state of modern computational tools, are poised to find new life in the robotic perception systems of the next decade.
Journal ArticleDOI
Volumetric Next-best-view Planning for 3D Object Reconstruction with Positioning Error
TL;DR: A next best view (NBV) algorithm that determines each view to reconstruct an arbitrary object and a method to deal with the uncertainty in sensor positioning is proposed.
Journal ArticleDOI
Active Visual Object Search in Unknown Environments Using Uncertain Semantics
TL;DR: It is argued that by making use of uncertain semantics of the environment, a robot tasked with finding an object can devise efficient search strategies that can locate everyday objects at the scale of an entire building floor, which is previously unknown to the robot.
References
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