Ihsan Baqer (8 results)

Condition: New. pp. 228.

Taschenbuch. Condition: Neu. Modeling of 3D Grasping of Artificial Hand Under Dynamic Load | A Novel Approach to Control the Robotic Hand Grasping Process by Using Artificial Neural Network Algorithm | Ihsan A. Baqer (u. a.) | Taschenbuch | 228 S. | Englisch | 2015 | Scholars' Press | EAN 9783639761221 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, a novel design of fingertip to detect slipping of the grasped object under dynamic load conditions was proposed to measure the normal and tangential contact force components. The proposed design was treated with conventional sensors and has the ability to optimize the design of the contact region without the need to change the sensory system. The proposed design was modeled mathematically, starting with the derivation of the velocity kinematics for any point on the system elements (Arm, Hand and Grasped object) from the base coordinate to the contact point coordinate. Also, the kinematics of contact for the grasped object are derived to explain the relation between the contact forces on the surface of the object and the resultant external force which applied to the object. The artificial neural network was trained based on the patterns of force component ratio signals at slippage occurrence, in order to detect slippage according to understanding of the behavior of contact force component ratio with respect to the coefficient of friction at slip occurrence without the need to any knowledge about the grasped object characteristics. 228 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: A. Baqer IhsanDr. Ihsan A. Baqer:Lecturer in University of Technology-Iraq-Baghdad /Mechanical Engineering Department.In this book, a novel design of fingertip to detect slipping of the grasped object under dynamic load condition.

Condition: New. Print on Demand pp. 228.

Condition: New. PRINT ON DEMAND pp. 228.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, a novel design of fingertip to detect slipping of the grasped object under dynamic load conditions was proposed to measure the normal and tangential contact force components. The proposed design was treated with conventional sensors and has the ability to optimize the design of the contact region without the need to change the sensory system. The proposed design was modeled mathematically, starting with the derivation of the velocity kinematics for any point on the system elements (Arm, Hand and Grasped object) from the base coordinate to the contact point coordinate. Also, the kinematics of contact for the grasped object are derived to explain the relation between the contact forces on the surface of the object and the resultant external force which applied to the object. The artificial neural network was trained based on the patterns of force component ratio signals at slippage occurrence, in order to detect slippage according to understanding of the behavior of contact force component ratio with respect to the coefficient of friction at slip occurrence without the need to any knowledge about the grasped object characteristics.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 228 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, a novel design of fingertip to detect slipping of the grasped object under dynamic load conditions was proposed to measure the normal and tangential contact force components. The proposed design was treated with conventional sensors and has the ability to optimize the design of the contact region without the need to change the sensory system. The proposed design was modeled mathematically, starting with the derivation of the velocity kinematics for any point on the system elements (Arm, Hand and Grasped object) from the base coordinate to the contact point coordinate. Also, the kinematics of contact for the grasped object are derived to explain the relation between the contact forces on the surface of the object and the resultant external force which applied to the object. The artificial neural network was trained based on the patterns of force component ratio signals at slippage occurrence, in order to detect slippage according to understanding of the behavior of contact force component ratio with respect to the coefficient of friction at slip occurrence without the need to any knowledge about the grasped object characteristics.