Giuseppe Averta

Human-Aware Robotics: Modeling Human Motor Skills for the Design, Planning and Control of a New Generation of Robotic Devices (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book moves from a thorough investigation of human capabilities during movements and interactions with objects and environment and translates those principles into the design planning and control of innovative mechatronic systems, providing significant advancements in the fields of human-robot interaction, autonomous robots, prosthetics and assistive devices. The work presented in this monograph is characterized by a significant paradigmatic shift with respect to typical approaches, as it always place the human at the center of the technology developed, and the human represents the starting point and the actual beneficiary of the developed solutions.

The content of this book is targeted to robotics and neuroscience enthusiasts, researchers and makers, students and simple lovers of the matter.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 276
• Erscheinungstermin: 25. Januar 2022
• Englisch
• ISBN-13: 9783030925215
• Artikelnr.: 63362338

Inhaltsangabe

Introduction.- Part I: Taming the Complexity of Human Motion Generation.- Understanding the Principal Modes of Natural Movements in Temporal Domain.- Quantifying the Time-Invariance Properties of Upper Limb Synergies.- Evidences on the Hierarchical Control of Human Hands.- Part II: On the Design of Nature-Inspired Prostheses and the Assessment of Motion Impairment.- Using Nature-Inspired Principles to Design of Robotic Limbs: the Soft Wrist.- A Novel Approach to Quantify Motion Impairment.- A novel mechatronic system for evaluating elbow muscular spasticity relying on Tonic Stretch Re ex Threshold estimation.- Part III: Transferring Human Principles to Cobots and Autonomous Robots.- Natural Motion: Embedding Human-Likeliness in Robot Movements.- A Focus on Motion Dynamics: Planning Impedance Behaviors in Physical Interaction.- Learning from Humans How to Grasp: a Reactive-Based Approach.- Learning from Humans How to Grasp: Enhancing the Reaching Strategy.- Learning to prevent grasp failure with soft hands: from on-line prediction to dual-arm grasp recovery.- Dexterity Augmentation of Robotic Hands: a Study on the Kinetic Domain.- Exploiting Principal Components for Robots Walking: an Approach for Sub-Optimal Locomotion.- Conclusions and Lessons Learned.