Designing Robot Behavior in Human-Robot Interactions
暫譯: 設計人機互動中的機器人行為
Liu, Changliu, Tang, Te, Lin, Hsien-Chung
- 出版商: CRC
- 出版日期: 2019-09-25
- 售價: $7,400
- 貴賓價: 9.5 折 $7,030
- 語言: 英文
- 頁數: 256
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367179695
- ISBN-13: 9780367179694
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相關分類:
機器人製作 Robots
海外代購書籍(需單獨結帳)
相關主題
商品描述
In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through control, planning, decision and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency in real-time robot motion planning, imitation of human behaviors from demonstration, dexterity of robots to adapt to different environments and tasks, cooperation among robots and humans with conflict resolution. These methods are applied in various scenarios, such as human-robot collaborative assembly, robot skill learning from human demonstration, interaction between autonomous and human-driven vehicles, etc.
Key Features:
- Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions.
- Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications.
- Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.
商品描述(中文翻譯)
在本書中，我們建立了一個統一的分析框架，用於各種人機系統，這些系統涉及同儕之間的互動（無論是空間共享或時間共享）或層級互動。我們提出了一種設計機器人行為的方法論，涵蓋控制、規劃、決策和學習。特別地，以下主題將深入討論：人機互動中的安全性、實時機器人運動規劃的效率、從示範中模仿人類行為、機器人對不同環境和任務的靈活性、以及機器人與人類之間的合作及衝突解決。這些方法應用於各種場景，例如人機協作組裝、機器人從人類示範中學習技能、自主車輛與人駕駛車輛之間的互動等。
主要特點：
- 提出一個統一框架，以建模和分析不同互動模式下的人機互動。
- 系統性地討論控制、決策和學習算法，使機器人能夠在各種應用中安全地與人類互動。
- 提供大量實驗研究，涵蓋工業協作機器人手臂和自主車輛。
作者簡介
Changliu Liu is an assistant professor in the Robotics Institute at Carnegie Mellon University, where she leads the Intelligent Control Lab. She received her PhD degree from University of California at Berkeley in 2017. Her research interests include: robotics and human-robot interactions, control and motion planning, optimization and optimal control, multi-agent system and game theory, design and verification of safe intelligent systems.
Te Tang received his PhD degree from University of California at Berkeley in 2018. He joined FANUC America Corporation in 2018, and he is currently a researcher at FANUC Advanced Research Laboratory. His research interests include robotics, learning from demonstration, computer vision and their industrial applications.
Hsien-Chung Lin is a research engineer in FANUC Advanced Research Laboratory at FANUC America Corporation. Prior to joining FANUC, he received his Ph.D. degree from University of California at Berkeley in 2018. His research interests cover robotics, optimal control, human-robot interaction, learning from demonstration and motion planning.
Masayoshi Tomizuka received his PhD degree from MIT in 1974. In 1974, he joined the Mechanical Engineering Department of the University of California, Berkeley, where he currently is Cheryl and John Neerhout, Jr., Distinguished Professor. His research interests are control theory and its applications to mechatronic systems such as robots. He is a Life Fellow of ASME and IEEE, and a Fellow of IFAC. He was awarded the Rufus Oldenburger Medal (2002) and the Richard Bellman Control Heritage Award (2018).
作者簡介(中文翻譯)
劉長流是卡內基梅隆大學機器人研究所的助理教授，負責智能控制實驗室的工作。她於2017年在加州大學伯克利分校獲得博士學位。她的研究興趣包括：機器人技術與人機互動、控制與運動規劃、優化與最優控制、多智能體系統與博弈論、安全智能系統的設計與驗證。
唐特於2018年在加州大學伯克利分校獲得博士學位。他於2018年加入FANUC美國公司，目前是FANUC先進研究實驗室的研究員。他的研究興趣包括機器人技術、示範學習、計算機視覺及其在工業中的應用。
林賢忠是FANUC美國公司FANUC先進研究實驗室的研究工程師。在加入FANUC之前，他於2018年在加州大學伯克利分校獲得博士學位。他的研究興趣涵蓋機器人技術、最優控制、人機互動、示範學習和運動規劃。
冨塚正義於1974年在麻省理工學院獲得博士學位。1974年，他加入加州大學伯克利分校的機械工程系，目前擔任Cheryl和John Neerhout, Jr.傑出教授。他的研究興趣是控制理論及其在機電系統（如機器人）中的應用。他是ASME和IEEE的終身會士，以及IFAC的會士。他曾獲得Rufus Oldenburger獎章（2002年）和Richard Bellman控制遺產獎（2018年）。
