Shape description and grasping for robot hand-eye coordination

Rao, K. Venkat; Medioni, Gérard; Liu, H.; Bekey, George A.

doi:10.1109/37.16767

Cited by 18 publications

(4 citation statements)

References 17 publications

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“…Instead of geometric CAD models, these approaches use more symbolic description of the objects, either based on volumetric primitives [8,9], or precomputed models of the objects, matched through vision [10]. Alternatively, they use a previous knowledge of grasp prototypes [11], that are adapted to particular object by using predefined rules or sensor feedback [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Vision-based three-finger grasp synthesis constrained by hand geometry

Morales

Sanz

Pobil

et al. 2006

Robotics and Autonomous Systems

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Section: Introductionmentioning

confidence: 99%

Vision-based three-finger grasp synthesis constrained by hand geometry

Morales

Sanz

Pobil

et al. 2006

Robotics and Autonomous Systems

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“…Reviews of light stripe scanning and related range sensing methods can be found in Hebert (2000), Bastuscheck (1989), and Besl (1988). Range sensing is an important component of many robotic applications, and light stripe ranging has been applied to a variety of robotic tasks including navigation (Nygards, Högström, and Wernersson 2000;Aldon and LeBris 1994), obstacle detection (Haverinen and Röning 1998), object recognition for grasping (Alshawish and Allen 1995;Rao et al 1989), and visual servoing (Khadraoui et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Stereoscopic Light Stripe Scanning: Interference Rejection, Error Minimization and Calibration

Taylor

Kleeman

2004

The International Journal of Robotics Research

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This paper addresses the problem of rejecting interference due to secondary specular reflections, cross-talk and other mechanisms in an active light stripe scanner for robotic applications. Conventional scanning methods control the environment to ensure the brightness of the stripe exceeds that of all other features. However, this assumption is likely to be violated for a robot operating in an uncontrolled environment. Robust scanning methods already exist, but suffer from problems including assumed scene structure, acquisition delay, lack of error recovery, and incorrect modeling of measurement noise. We propose a robust technique that overcomes these problems, using two cameras and knowledge of the light plane orientation to disambiguate the primary reflection from spurious measurements. Unlike other robust techniques, our validation and reconstruction algorithms are optimal with respect to sensor noise. Furthermore, we propose a procedure to calibrate the system using measurements of an arbitrary non-planar target, providing robust validation independently of ranging accuracy. Finally, our robust techniques allow the sensor to operate in ambient indoor light, allowing color and range to be implicitly registered. An experimental scanner demonstrates the effectiveness of the proposed techniques. Source code and sample data are provided in the multimedia extensions.

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“…As a data-driven approach for grasping, Rao et al 13 used range data as visual images to obtain a circular Generalized Cylinders (GCs) representation. They compute the 3-D axis and the sweeping function of cross sections of GCs 14 from edge lines of the range data by an iterative and ad hoc method.…”

Section: Introductionmentioning

confidence: 99%

Binocular vision planning with anthropomorphic features for grasping parts by robots

Chung¹,

Nagata²

1996

Robotica

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SUMMARYPlanning of an active vision having anthropomorphic features, such as binocularity, foveas and gaze control, is proposed. The aim of the vision is to provide robots with the pose informaton of an adequate object to be grasped by the robots. For this, the paper describes a viewer-oriented fixation point frame and its calibration, active motion and gaze control of the vision, disparity filtering, zoom control, and estimation of the pose of a specific portion of a selected object. On the basis of the importance of the contour information and the scheme of stereo vision in recognizing objects by humans, the occluding contour pairs of objects are used as inputs in order to show the proposed visual planning.

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Shape description and grasping for robot hand-eye coordination

Cited by 18 publications

References 17 publications

Vision-based three-finger grasp synthesis constrained by hand geometry

Vision-based three-finger grasp synthesis constrained by hand geometry

Stereoscopic Light Stripe Scanning: Interference Rejection, Error Minimization and Calibration

Binocular vision planning with anthropomorphic features for grasping parts by robots

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