Neural network control of multifingered robot hands using visual feedback
IEEE Transactions on Neural Networks
ACC'09 Proceedings of the 2009 conference on American Control Conference
A darboux-frame-based formulation of spin-rolling motion of rigid objects with point contact
IEEE Transactions on Robotics
Short survey: Dual arm manipulation-A survey
Robotics and Autonomous Systems
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This paper proposes a method for controlling an object with parallel surfaces in a horizontal plane by a pair of finger robots. The control method can achieve stable grasping, relative orientation control, and relative position control of the grasped object. The control inputs require neither any object parameters nor any object sensing, such as tactile sensors, force sensors, or visual sensors. The control inputs are also quite simple and do not need to solve either inverse kinematics or inverse dynamics. The stability of the closed-loop system is proved, and simulation and experimental results validate the control method.