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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...
This paper describes a topological SLAM system using a purely vision-based approach. This robot utilizes a GPU-based omnidirectional catadioptric stereovision system to perceive and plan its path in the environment. Subsequently, the omnidirectional images generated are used to incrementally build a database of image signatures based on the standard 2D Haar Wavelet decomposition. In order to maintain...
The research presented introduces a new methodology to infer environment structure and robot localization by using a monocular machine vision system. The local field of view is constrained to the vicinity of the mobile robot in order to accomplish with robust navigation issues. The strategy proposed uses optical flow techniques and planar models to obtain qualitative 3D information and robot localization...
Online coordination of visual information with slow speed manipulator control is studied in the specific task of three dimensional robotic catching using position based visual servoing. The problem involves the design and application of a recursive algorithm to extract and predict the position of an object in a 3D environment from one feature correspondence from a monocular image sequence. The measured...
The Helmholtz-Hodge decomposition separates a vector filed into translation, rotation, and divergent vector fields. In this paper, using the Helmholtz-Hodge decomposition of omnidirectional optical flow field, we develop geometric algorithms for the detection of free space and navigation direction. For free space direction and navigation, we use catadioptric image sequences and spherical image sequence,...
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