| Description |
1 online resource |
| Contents |
Part I: Tactile sensing and perception. 1. GelTip tactile sensors for dexterous manipulation in clutter / Daniel Fernandes Gomes Shan Luo -- 2. Robotic perception of object properties using tactile sensing/ Jiaqi Jiang Shan Luo -- 3. Multimodal perception for dexterous manipulation / Guanqun Cao Shan Luo -- 4. Capacitive Material Detection with Machine Learning for Robotic Grasping applications / Hannes Kisner Yitao Ding Ulrike Thomas -- Part II: Skill representation and learning. 5. Admittance control: learning from humans through collaborating with humans / Ning Wang Chenguang Yang -- 6. Sensorimotor Control for Dexterous Grasping - Inspiration from human hand / Ke Li -- 7. From human to robot grasping: force and kinematic synergies / Abdeldjallil Naceri Nicolò Boccardo Lorenzo Lombardi Andrea Marinelli Diego Hidalgo Sami Haddadin Matteo Laffranchi Lorenzo De Michieli -- 8. Learning form-closure grasping with attractive region in environment / Rui Li Zhenshan Bing Qi Qi -- 9. Learning hierarchical control for robust in-hand manipulation / Tingguang Li -- 10. Learning Industrial Assembly by Guided-DDPG / Yongxiang Fan -- Part III: Robotic hand adaptive control. 11. Clinical evaluation of Hannes: measuring the usability of a novel poly-articulated prosthetic hand / Marianna Semprini Nicolò Boccardo Andrea Lince Simone Traverso Lorenzo Lombardi Antonio Succi Michele Canepa Valentina Squeri Jody A. Saglia Paolo Ariano Luigi Reale Pericle Rando Simona Castellano Emanuele Gruppioni Mattero Laffranchi Lorenzo De Michieli -- 12. A hand-arm teleoprtation system for robotic dexterous manipulation / Shuang Li Qiang Li Jianwei Zhang -- 13. Neural Network-enhanced Optimal motion planning for robot manipulation under remote center of motion / Hang Su Chenguang Yang -- 14. Towards Dexterous In-Hand Manipulation of Unknown Objects / Qiang Li Robert Maschke Helge Ritter -- 15. Robust dexterous manipulation and finger gaiting under various uncertainties / Yongxiang Fan -- A. Key components of dexterous manipulation: tactile sensing, skill learning, and adaptive control / Qiang Li Shan Luo Zhaopeng Chen Chenguang Yang Jianwei Zhang. |
| Summary |
Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on cross-disciplinary lines of research and groundbreaking research ideas in three research lines: tactile sensing, skill learning and dexterous control. The book introduces recent work about human dexterous skill representation and learning, along with discussions of tactile sensing and its applications on unknown objects' property recognition and reconstruction. Sections also introduce the adaptive control schema and its learning by imitation and exploration. Other chapters describe the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in related branches. The book summarizes the different approaches and discusses the pros and cons of each. Chapters not only describe the research but also include basic knowledge that can help readers understand the proposed work, making it an excellent resource for researchers and professionals who work in the robotics industry, haptics and in machine learning. Provides a review of tactile perception and the latest advances in the use of robotic dexterous manipulation Presents the most detailed work on synthesizing intelligent tactile perception, skill learning and adaptive control Introduces recent work on human's dexterous skill representation and learning and the adaptive control schema and its learning by imitation and exploration Reveals and illustrates how robots can improve dexterity by modern tactile sensing, interactive perception, learning and adaptive control approaches. |
| Subject |
Robot hands.
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Robotics.
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Tactile sensors.
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Robotics |
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Préhenseurs.
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Robotique.
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Capteurs tactiles.
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Robot hands
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Robotics
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Tactile sensors
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| Added Author |
Li, Qiang.
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| Other Form: |
Print version: 0323904459 9780323904452 (OCoLC)1268114153 |
| ISBN |
9780323904179 (electronic bk.) |
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0323904173 (electronic bk.) |
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9780323904452 |
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0323904459 |
| Standard No. |
AU@ 000071513161 |
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AU@ 000074360441 |
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