Knowledge-based robotic grasping

Conference · Sun Jan 01 00:00:00 EST 1989

DOI:https://doi.org/10.1109/ROBOT.1990.126173· OSTI ID:7007155

Stansfield, S. A.

In this paper, we describe a general-purpose robotic grasping system for use in unstructured environments. Using computer vision and a compact set of heuristics, the system automatically generates the robot arm and hand motions required for grasping an unmodeled object. The utility of such a system is most evident in environments where the robot will have to grasp and manipulate a variety of unknown objects, but where many of the manipulation tasks may be relatively simple. Examples of such domains are planetary exploration and astronaut assistance, undersea salvage and rescue, and nuclear waste site clean-up. This work implements a two-stage model of grasping: stage one is an orientation of the hand and wrist and a ballistic reach toward the object; stage two is hand preshaping and adjustment. Visual features are first extracted from the unmodeled object. These features and their relations are used by an expert system to generate a set of valid reach/grasps for the object. These grasps are then used in driving the robot hand and arm to bring the fingers into contact with the object in the desired configuration. 16 refs., 14 figs.

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: DOE/DP
• DOE Contract Number: AC04-76DP00789
• OSTI ID: 7007155
• Report Number(s): SAND-89-2044C; CONF-900559-9; ON: DE90007216
• Resource Relation: Conference: IEEE robotics and automation conference, Cincinnati, OH (USA), 13-18 May 1990
• Country of Publication: United States
• Language: English

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
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420203* - Engineering- Handling Equipment & Procedures
320201 - Energy Conservation
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990200 - Mathematics & Computers