Robotic Grasping of Novel Objects using Vision
International Journal of Robotics Research
Learning grasp strategies with partial shape information
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Data-driven grasping with partial sensor data
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Autonomous Robots
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We investigate "intelligent" grasping schemes using a fuzzy logic rule base expert system. We use a vision system, robot arm and mechanical hand to locate and manipulate unmodeled, randomly placed objects of various sizes and shapes. In the pregrasp stage, we use vision data to provide a nonlinear mapping from object characteristics to hand configuration. In the postgrasp stage, we use hand data to ascertain the security of the grasp. Computational geometry is used to gauge the quality of the grasp and to quantify and validate the choice of hand configurations generated by the fuzzy logic expert system. The system is implemented within a low-cost virtual collaborative environment.