© 2010

Robot Intelligence

An Advanced Knowledge Processing Approach

  • Honghai Liu
  • Dongbing Gu
  • Robert J. Howlett
  • Yonghuai Liu

Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Alexander Skoglund, Boyko Iliev, Rainer Palm
    Pages 1-23
  3. Rainer Palm, Boyko Iliev, Bourhane Kadmiry
    Pages 25-47
  4. Xiaofei Ji, Honghai Liu, Yibo Li
    Pages 71-93
  5. Huiyu Zhou, Andrew M. Wallace, Patrick R. Green
    Pages 117-141
  6. Jiandong Tian, Yandong Tang
    Pages 143-167
  7. Yonghuai Liu, Ala Al-Obaidi, Anthony Jakas, Junjie Liu
    Pages 169-190
  8. John Oyekan, Bowen Lu, Bo Li, Dongbing Gu, Huosheng Hu
    Pages 209-228
  9. James Ballantyne, Edward Johns, Salman Valibeik, Charence Wong, Guang-Zhong Yang
    Pages 245-268
  10. Back Matter
    Pages 291-293

About this book


Robot Intelligence is an exciting interdisciplinary field including engineering, information technology, machine learning, biological science and psychology. Its dramatic growth in practical applications is driven by both real-world requirements and maturity of related disciplines such as intelligent algorithms. It is expected that perception, understanding and reasoning capabilities play a crucial role in robot-assisted tasks and enable robots to exhibit similar performance on executing various tasks in both constrained and unconstrained environments.

Robot Intelligence is a rare collection of chapters reflecting recent robotics developments from the advanced knowledge processing perspective. It also provides a comprehensive introduction and methodology to selected robotics topics including human robot interaction, human motion analysis, robot vision and advanced control. The robot intelligence methods presented enable readers to address many complex problems involving a wide range of robot sensors for the perception and understanding of the environment and the reasoning of the subsequent actions. The book’s comprehensive coverage will prove invaluable to senior undergraduates, PhD students, researchers and practitioners.


artificial intelligence autonom communication genetic programming hidden markov model intelligence knowledge base learning mobile robot navigation programming robot robot vision robotics unmanned aerial vehicle

Editors and affiliations

  • Honghai Liu
    • 1
  • Dongbing Gu
    • 2
  • Robert J. Howlett
    • 3
  • Yonghuai Liu
    • 4
  1. 1.School of Creative TechnologiesThe University of PortsmouthPortsmouthUnited Kingdom
  2. 2.Department of Computer ScienceUniversity of EssexWivenhoe ParkUnited Kingdom
  3. 3., School of EngineeringUniversity of BrightonBrightonUnited Kingdom
  4. 4.Department of Computer ScienceUniversity of WalesAberystwythUnited Kingdom

About the editors

Dr. Honghai Liu is a Reader and Head of Intelligent Systems & Robotics Research Group (ISR), School of Creative Technologies, at the University of Portsmouth. He previously held research appointments at the Departments of Computing Science and Engineering in the Universities of London and Aberdeen, and project leader appointments in large-scale industrial control and system integration industry. Honghai has published over 150 refereed journal and conference papers including three Best Paper Awards. He is interested in approximate computation, machine intelligence, pattern recognition and their practical applications with an emphasis on approaches which could make contribution to the intelligent connection of perception to action in systems context. For this emphasis, he has been developing a framework based on approximate computing and it has been implemented into human motion analysis, multifingered robot manipulation, data novelty detection and intelligent control for electric vehicle suspensions with substantial results. He is a Senior Member of IEEE and a Member of IET.

Dongbing Gu’s current research interests include multi-agent systems, wireless sensor networks, distributed control  algorithms, distributed information fusion, cooperative control, reinforcement learning, fuzzy logic and neural network based motion control, model predictive control, wavelet multi-scale image edge detection, and Bayesian multi-scale image segmentation. His work combines fundamental concepts and tools from computer science, networks, systems and control theory.

Robert Howlett has considerable expertise in the use of Intelligent Systems in the solution of industrial problems.  He has been successful in applying neural networks, expert & fuzzy methods, web intelligence and related technology to: Sustainability: renewable energy, measurement, control, simulation and modeling of energy systems; Condition monitoring: diagnostic tools and systems; fault location and identification; virtual sensors; Automotive electronics: engine management systems; monitoring and control of small engines. He is the Executive Chair of the UKES Internationalorganization, which facilitates knowledge transfer and research in areas including Intelligent Systems, Sustainability, and Knowledge Transfer. Through the UKES Smart Systems Centre he provides consultancy services on, for example, Knowledge Transfer Partnerships the EU Interreg Anglo-French funding programme, and technical subjects within his expertise. By setting up and managing over 20 collaborative projects with SMEs and other companies, managing the University of Brighton Knowledge Transfer Partnerships (KTP) Centre for a number of years, and Chairmanship of the KTP National Forum, he has become nationally recognised in knowledge and technology transfer, the commercialisation of research, and the third-mission agenda.

Dr Yonghuai Liu has completed BSc and MSc studies and also holds two PhDs. Younghuai gained solid knowledge in the fields of Geography, Cartography, Mathematics, and Economics whilst studying for the BSc degree. Whilst studying for the MSc degree he gained knowledge in the fields of Pattern Recognition, Image Processing, and Mathematics. PhD study in China which gave him solid knowledge in the fields of Artificial Intelligence, Uncertain Reasoning, and also Mathematics. During this period of time, Yonghuai researched on Uncertain Reasoning, Expert Systems, Artificial Intelligence, Pattern Recognition, Image Processing, and Multimedia and taught both undergraduate and postgraduate courses on Artificial Intelligence, Discrete Mathematics, Combinatorial Mathematics, and Multimedia. Younghuai received the ORS award. As a result, he studied for his second PhD degree at The University of Hull under the supervision of Dr Marcos A Rodrigues. He is currently a lecturer at the Department of Computer Science, The University of Wales, Aberystwyth.

Bibliographic information

  • Book Title Robot Intelligence
  • Book Subtitle An Advanced Knowledge Processing Approach
  • Editors Honghai Liu
    Dongbing Gu
    Robert J. Howlett
    Yonghuai Liu
  • Series Title Advanced Information and Knowledge Processing
  • Series Abbreviated Title Adv.Informat.Knowledge Processing (formerly:KIM-Knowled.Inform.Manag)
  • DOI
  • Copyright Information Springer-Verlag London Limited 2010
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Hardcover ISBN 978-1-84996-328-2
  • Softcover ISBN 978-1-4471-2582-2
  • eBook ISBN 978-1-84996-329-9
  • Series ISSN 1610-3947
  • Edition Number 1
  • Number of Pages XIV, 294
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Artificial Intelligence
    Robotics and Automation
  • Buy this book on publisher's site
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From the reviews:

“This book’s 13 chapters are a unique collection of research in which machine learning extends into robotic intelligence in order to develop robots that are more complex and adaptable to their dynamic environments. … There is something here for everyone great ideas, sufficient theoretical backups, and excellent case studies with real robots in action. Summing Up: Highly recommended. Upper-division undergraduates and above.” (G. Trajkovski, Choice, Vol. 48 (7), March, 2011)

“This book was a welcome surprise: it is short, but includes many topics relevant to the robotics research community. … Another interesting aspect of the book is that almost every chapter includes physical experiments. … Researchers and PhD students interested in the latest approaches and techniques in robotics will be most interested in this book. It is especially appropriate for researchers interested in the fields of manipulator robots and social robots (robots that interact with human beings).” (Ramon Gonzalez Sanchez, ACM Computing Reviews, January, 2012)