Title:

Hand-eye coordination for grasping moving objects

Author(s):

Allen, Peter K.
Timcenko, Aleksandar
Yoshimi, Billibon
Michelman, Paul

Date:

1991

Type:

Articles

Department:

Computer Science

Permanent URL:

http://hdl.handle.net/10022/AC:P:15264

Part Number:

1383

Book/Journal Title:

Sensor Fusion III: 3D Perception and Recognition

Book Author:

Schenker, Paul S.

Publisher:

Society of Photo-optical Instrumentation Engineers

Publisher Location:

Bellingham, Wash.

Abstract:

Most robotic grasping tasks assume a stationary or fixed object. In this paper, we explore the requirements for grasping a moving object. This task requires proper coordination between at least 3 separate subsystems: dynamic vision sensing, real-time arm control, and grasp control. As with humans, our system first visually tracks the object's 3-D position. Because the object is in motion, this must be done in a dynamic manner to coordinate the motion of the robotic arm as it tracks the object. The dynamic vision system is used to feed a real-time arm control algorithm that plans a trajectory. The arm control algorithm is implemented in two steps: 1) filtering and prediction, and 2) kinematic transformation computation. Once the trajectory of the object is tracked, the hand must intercept the object to actually grasp it. We present 3 different strategies for intercepting the object and results from the tracking algorithm.

Subject(s):

Robotics

DOI:

http://dx.doi.org/10.1117/12.25255

Item views:

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