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Integrating vision and touch for object recognition tasks

Peter K. Allen
- pp 407-440
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TLDR
In this paper, a robotic system for object recognition that uses passive stereo vision and active exploratory tactile sensing is described, where the complementary nature of these sensing modalities allows the system to discover the underlying 3D structure of the objects to be recognized.
Abstract
A robotic system for object recognition is described that uses passive stereo vision and active exploratory tactile sensing. The complementary nature of these sensing modalities allows the system to discover the underlying 3-D structure of the objects to be recognized. This structure is embodied in rich, hierarchical, viewpoint-independent 3-D models of the objects which include curved surfaces, concavities and holes. The vision processing provides sparse 3-D data about regions of interest that are then actively explored by the tactile sensor mounted on the end of a six-degree-of-freedom manipulator. A robust, hierarchical procedure has been developed to inte grate the visual and tactile data into accurate 3-D surface and feature primitives. This integration of vision and touch provides geometric measures of the surfaces and features that are used in a matching phase to find model objects that are consistent with the sensory data. Methods for verification of the hypothesis are presented, including the sen...

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Journal ArticleDOI

Multisensor integration and fusion in intelligent systems

TL;DR: The issues involved in integrating multiple sensors into the operation of a system are presented in the context of the type of information these sensors can uniquely provide, along with proposed high-level multisensory representations suitable for mobile robot navigation and control.
Journal ArticleDOI

Dempster-Shafer theory for sensor fusion in autonomous mobile robots

TL;DR: Dempster-Shafer (DS) theory in terms of its utility for sensor fusion for autonomous mobile robots is discussed, exploiting the weight of conflict metric and the enlargement of the frame of discernment to allow a modular decomposition of evidence.
Proceedings ArticleDOI

Object identification with tactile sensors using bag-of-features

TL;DR: A novel approach for identifying objects using touch sensors installed in the finger tips of a manipulation robot by means of unsupervised clustering on training data, which learns a vocabulary from tactile observations which is used to generate a histogram codebook.
Journal ArticleDOI

Visual–Tactile Fusion for Object Recognition

TL;DR: The multivariate-time-series model is used to represent the tactile sequence and the covariance descriptor to characterize the image, and a joint group kernel sparse coding method is designed to tackle the intrinsically weak pairing problem in visual–tactile data samples.
Journal ArticleDOI

Minimal representation multisensor fusion using differential evolution

TL;DR: Experiments in robot manipulation using both tactile and visual sensing demonstrate that this minimal representation multisensor fusion algorithm is effective in finding useful and practical solutions to this problem for real systems.
References
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Computational Geometry for Design and Manufacture

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TL;DR: In this paper, the mathematical techniques for the representation, analysis and synthesis of shape information by computers are discussed, and splines and related means for defining composite curves and "patched" surfaces are discussed.
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Symbolic reasoning among 3-D models and 2-D images

TL;DR: Modelling, prediction, description and interpretation proceed concurrently from coarse object subpart and class interpretations of images, to fine distinctions among object subclasses and more precise three dimensional quantification of objects.
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