Robot hands and the mechanics of manipulation
Robot hands and the mechanics of manipulation
Dextrous robot hands
Human grasp choice and robotic grasp analysis
Dextrous robot hands
Opposition space and human prehension
Dextrous robot hands
Intelligent exploration by the human hand
Dextrous robot hands
CONDOR: a computational architecture for robots
Dextrous robot hands
Tactile sensing for shape interpretation
Dextrous robot hands
Robot grasp synthesis algorithms: a survey
International Journal of Robotics Research
Biologically inspired approaches to robotics: what can we learn from insects?
Communications of the ACM
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Experiments in Hand-Eye Coordination Using Active Vision
The 4th International Symposium on Experimental Robotics IV
A neural network based hierarchical motor schema of a multi-finger hand and its motion diversity
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
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This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image.The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.