Robot hands and the mechanics of manipulation
Robot hands and the mechanics of manipulation
Handey: a robot task planner
Machine Learning
Mathematical Programming: Series A and B
Let them fall where they may: capture regions of curved objects and polyhedra
International Journal of Robotics Research
Robotics in Practice: Management and Applications of Robotics in Industry
Robotics in Practice: Management and Applications of Robotics in Industry
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Springer Handbook of Robotics
Robotic Grasping of Novel Objects using Vision
International Journal of Robotics Research
A versatile computer-controlled assembly system
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane
IEEE Transactions on Pattern Analysis and Machine Intelligence
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While complex hands seem to offer generality, simple hands are often more practical. This raises the question: how do generality and simplicity trade off in the design of robot hands? This paper explores the tension between simplicity in hand design and generality in hand function. It raises arguments both for and against simple hands, it considers several familiar examples, and it proposes an approach for autonomous manipulation using a general-purpose but simple hand. We explore the approach in the context of a bin-picking task, focused on grasping, recognition, and localization. The central idea is to use learned knowledge of stable grasp poses as a cue for object recognition and localization. This leads to some novel design criteria, such as minimizing the number of stable grasp poses. Finally, we describe experiments with two prototype hands to perform bin-picking of highlighter markers.