Integration of robust visual perception and control for a domestic humanoid robot

Taylor, Geoffrey; Kleeman, Lindsay

doi:10.1109/iros.2004.1389485

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…A recent work by Taylor et al [18] uses a similar full system assembly as we do. They, too, combine a laser scanner with vision but stereo instead of monocular.…”

Section: State Of the Artmentioning

confidence: 99%

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An Integration Concept for Vision-Based Object Handling: Shape-Capture, Detection and Tracking

Schlemmer

Biegelbauer

Vincze

2006

Advances in Machine Vision, Image Processing, and Pattern Analysis

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Combining visual shape-capturing and vision-based object manipulation without intermediate manual interaction steps is important for autonomic robotic systems. In this work we introduce the concept of such a vision system closing the chain of shape-capturing, detecting and tracking. Therefore, we combine a laser range sensor for the first two steps and a monocular camera for the tracking step. Convex shaped objects in everyday cluttered and occluded scenes can automatically be re-detected and tracked, which is suitable for automated visual servoing or robotic grasping tasks. The separation of shape and appearance information allows different environmental and illumination conditions for shape-capturing and tracking. The paper describes the framework and its components of visual shape-capturing, fast 3D object detection and robust tracking. Experiments show the feasibility of the concept.

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“…A recent work by Taylor et al [18] uses a similar full system assembly as we do. They, too, combine a laser scanner with vision but stereo instead of monocular.…”

Section: State Of the Artmentioning

confidence: 99%

“…2.2). That way, we avoid the computational expensive segmentation and enable the handling of convex objects with less geometric constraints than [18].…”

Section: State Of the Artmentioning

confidence: 99%

An Integration Concept for Vision-Based Object Handling: Shape-Capture, Detection and Tracking

Schlemmer

Biegelbauer

Vincze

2006

Advances in Machine Vision, Image Processing, and Pattern Analysis

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“…(3) The human hand-eye system is based on the position visual feedback servoing system. (4) Binocular vision system, although not required, but increases the efficiency of movement [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Object Manipulation Control Strategy Analysis Center of Humanoid Robot

Dai

2011

AMR

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This document The visual is the main senses of human to capture the information, is also considered the most important apperceive component of the robot. Images information obtained by the visual sensor as a feedback, which can be constructed robot position closed loop control, which is visual servoing. In the visual servoing, the purpose of images automatic acquisition and analysis is to achieve humanoid robot control, based on the machine vision principle, the humanoid robot accomplish the feedback information in the shortest possible time, which is obtained from the image direct feedback and fast processing, these constitute a closed-loop control of the robot's positionexplains and demonstrates how to prepare your camera-ready manuscript for Trans Tech Publications. The best is to read these instructions and follow the outline of this text. The text area for your manuscript must be 17 cm wide and 25 cm high (6.7 and 9.8 inches, resp.). Do not place any text outside this area. Use good quality, white paper of approximately 21 x 29 cm or 8 x 11 inches (please do not change the document setting from A4 to letter). Your manuscript will be reduced by approximately 20% by the publisher. Please keep this in mind when designing your figures and tables etc.

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“…A system similar to the setup proposed here has been presented by (Taylor, G. & Kleeman, L., 2004) and consists of a laser range scanner and stereo cameras. Detection of geometrically primitive objects (boxes, bowls, cylinders) is performed without previous learning and requires a previous scene segmentation using surface curvatures.…”

Section: Introductionmentioning

confidence: 99%

Rethinking Robot Vision – Combining Shape and Appearance

Schlemmer

Biegelbauer

Vincze

2007

International Journal of Advanced Robotic Systems

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Equipping autonomous robots with vision sensors provides a multitude of advantages by simultaneously bringing up difficulties with regard to different illumination conditions. Furthermore, especially with service robots, the objects to be handled must somehow be learned for a later manipulation. In this paper we summarise work on combining two different vision sensors, namely a laser range scanner and a monocular colour camera, for shape-capturing, detecting and tracking of objects in cluttered scenes without the need of intermediate user interaction. The use of different sensor types provides the advantage of separating the shape and the appearance of the object and therefore overcome the problem with changing illumination conditions. We describe the framework and its components of visual shape-capturing, fast 3D object detection and robust tracking as well as examples that show the feasibility of this approach.

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Integration of robust visual perception and control for a domestic humanoid robot

Cited by 9 publications

References 16 publications

An Integration Concept for Vision-Based Object Handling: Shape-Capture, Detection and Tracking

An Integration Concept for Vision-Based Object Handling: Shape-Capture, Detection and Tracking

Object Manipulation Control Strategy Analysis Center of Humanoid Robot

Rethinking Robot Vision – Combining Shape and Appearance

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