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Titlebook: Human and Robot Hands; Sensorimotor Synergi Matteo Bianchi,Alessandro Moscatelli Book 2016 Springer International Publishing AG, part of Sp

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楼主: CULT
发表于 2025-3-25 06:08:29 | 显示全部楼层
Book 2016s the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one...Human and Robot Hands .provides a valuable reference for students,
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Digit Position and Force Synergies During Unconstrained Graspingance was accounted by the first two components (corresponding to the first and the second force synergy). This is consisted with the framework of motor synergy, since two components successfully explained most of the variability in the data.
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From Soft to Adaptive Synergies: The Pisa/IIT SoftHandnce of application of the synthesis method of adaptive synergies, the Pisa/IIT SoftHand is described in detail. The hand has 19 joints, but only uses one actuator to activate its adaptive synergy. Of particular relevance in its design is the very soft and safe, yet powerful and extremely robust stru
发表于 2025-3-25 21:12:15 | 显示全部楼层
A Learn by Demonstration Approach for Closed-Loop, Robust, Anthropomorphic Grasp Planningrovides online feedback, performing object detection, object pose estimation and triggering the appropriate NF models. The NF models formulate a closed-loop velocity control scheme, that ensures humanlikeness of robot motion and guarantees convergence to the desired goals. The aforementioned scheme
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Incremental Learning of Muscle Synergies: From Calibration to Interactionimprove the stability and reliability of natural prosthetic control. Incremental learning enforces a true, endless adaptation of the prosthesis to the subject, the environment, the objects to be manipulated; and it allows for the adaptation of the subject to the prosthesis in the course of time, lea
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How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolboxn implemented using the SynGrasp Matlab toolbox. This tool includes functions for the definition of hand kinematic structure and of the contact points with a grasped object, the coupling between joints induced by a synergistic control, compliance at the contact, joint and actuator levels. Its analys
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Synergy-Based Optimal Sensing Techniques for Hand Pose Reconstructioneen neuroscience and robotic/artificial systems, showing how the findings achieved in one field can inspire and be used to advance the state of art in the other one, and vice versa. More specifically, our leading approach is to use the concept of kinematic synergies to optimally estimate the posture
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