Human-friendly robotics 2021 : HFR : 14th International Workshop on Human-Friendly Robotics / Gianluca Palli, Claudio Melchiorri, Roberto Meattini, editors.
2022
TJ211.49
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Title
Human-friendly robotics 2021 : HFR : 14th International Workshop on Human-Friendly Robotics / Gianluca Palli, Claudio Melchiorri, Roberto Meattini, editors.
ISBN
9783030963590 (electronic bk.)
3030963594 (electronic bk.)
9783030963583 (print)
3030963586
3030963594 (electronic bk.)
9783030963583 (print)
3030963586
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (1 volume) : illustrations (black and white, and color).
Item Number
10.1007/978-3-030-96359-0 doi
Call Number
TJ211.49
Dewey Decimal Classification
629.8/924019
Summary
This book is a collection of research results in a wide range of topics related to humanrobot interaction, both physical and cognitive, including theories, methodologies, technologies, and empirical and experimental studies. The works contained in the book have been presented at the 14th International Workshop on Human-Friendly Robotics (HFR 2021), organized by the University of Bologna (Bologna, Italy, October 2829, 2021), and they describe the most original achievements in the field of humanrobot interaction coming from the ideas of young researchers. The intended readership of the book is any researcher in the field of robotics interested to research problems related to humanrobot coexistence, like robot interaction control, robot learning, and humanrobot co-working.
Note
Selected conference papers.
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Access limited to authorized users.
Source of Description
Description based on print version record.
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Series
Springer proceedings in advanced robotics ; 23.
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Table of Contents
Combining Hybrid Genetic Algorithms and Feedforward Neural Net-works for Pallet Loading in Real- World Applications
Complete and consistent payload identification during human-robot collaboration: a safety oriented procedure
Deep Learning and OcTree-GPU-based ICP for Efficient 6D Model Registration of Large Objects.
Complete and consistent payload identification during human-robot collaboration: a safety oriented procedure
Deep Learning and OcTree-GPU-based ICP for Efficient 6D Model Registration of Large Objects.