Innovations in Intelligent Machines - 1

1. Front Matter

   Pages I-XIII

   PDF

2. Intelligent Machines: An Introduction

   • Lakhmi C. Jain, Anas Quteishat, Chee Peng Lim

   Pages 1-9

3. Predicting Operator Capacity for Supervisory Control of Multiple UAVs

   • M. L. Cummings, Carl E. Nehme, Jacob Crandall, Paul Mitchell

   Pages 11-37

4. Team, Game, and Negotiation based Intelligent Autonomous UAV Task Allocation for Wide Area Applications

   • P. B. Sujit, A. Sinha, D. Ghose

   Pages 39-75

5. UAV Path Planning Using Evolutionary Algorithms

   • Ioannis K. Nikolos, Eleftherios S. Zografos, Athina N. Brintaki

   Pages 77-111

6. Evolution-based Dynamic Path Planning for Autonomous Vehicles

   • Anawat Pongpunwattana, Rolf Rysdyk

   Pages 113-145

7. Algorithms for Routing Problems Involving UAVs

   • Sivakumar Rathinam, Raja Sengupta

   Pages 147-172

8. State Estimation for Micro Air Vehicles

   • Randal W. Beard

   Pages 173-199

9. Evolutionary Design of a Control Architecture for Soccer-Playing Robots

   • Steffen Prüter, Hagen Burchardt, Ralf Salomon

   Pages 201-222

10. Toward Robot Perception through Omnidirectional Vision

    • José Gaspar, Niall Winters, Etienne Grossmann, José Santos- Victor

    Pages 223-270

Innovations in Intelligent Machines is a very timely volume that takes a fresh look on the recent attempts of instilling human-like intelligence into computer-controlled devices. By contrast to the machine intelligence research of the last two decades, the recent work in this area recognises explicitly the fact that human intelligence is not purely computational but that it also has an element of empirical validation (interaction with the environment). Also, recent research recognises that human intelligence does not always prevent one from making errors but it equips one with the ability to learn from m- takes. The latter is the basic premise for the development of the collaborative (swarm)intelligencethatdemonstratesthevalueofthevirtualexperiencepool assembled from cases of successful and unsuccessful execution of a particular algorithm. The editors are to be complemented for their vision of designing a fra- work within which they ask some fundamental questions about the nature of intelligence in general and intelligent machines in particular and illustrate answers to these questions with speci?c practical system implementations in the consecutive chapters of the book.

• Unmanned Aerial Vehicles
• Unmanned Ground Vehicles
• algorithm
• algorithms
• architecture
• control
• design
• evolution
• evolutionary algorithm
• machine
• operator
• perception
• planning
• robot
• unmanned aerial vehicle

• Defence Science and Technology Organisation, Edinburgh, Australia

  Javaan Singh Chahl

• University of South Australia Mawson Lakes Campus, Adelaide, Australia

  Lakhmi C. Jain

• Odonatrix Pty Ltd., Adelaide, Australia

  Akiko Mizutani

• University of Tsukuba, Japan

  Mika Sato-Ilic

Policies and ethics