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Intelligent Planning for Mobile Robotics

Book Description

Robotics is an ever-expanding field and intelligent planning continues to play a major role. Given that the intention of mobile robots is to carry out tasks independent from human aid, robot intelligence is needed to make and plan out decisions based on various sensors. Planning is the fundamental activity that implements this intelligence into the mobile robots to complete such tasks. Understanding problems, challenges, and solutions to path planning and how it fits in is important to the realm of robotics. Intelligent Planning for Mobile Robotics: Algorithmic Approaches presents content coverage on the basics of artificial intelligence, search problems, and soft computing approaches. This collection of research provides insight on both robotics and basic algorithms and could serve as a reference book for courses related to robotics, special topics in AI, planning, applied soft computing, applied AI, and applied evolutionary computing. It is an ideal choice for research students, scholars, and professors alike. 

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Preface
  5. Acknowledgment
    1. PERMISSIONS
  6. Chapter 1: Introduction
    1. ABSTRACT
    2. INTRODUCTION
    3. PRELIMINARIES AND DEFINITIONS
    4. APPLICATIONS
    5. PROBLEM SOLVING IN ROBOTICS
    6. ROBOT MOTION PLANNING
    7. CONCLUSION
  7. Chapter 2: Graph Based Path Planning
    1. ABSTRACT
    2. INTRODUCTION
    3. GRAPHS
    4. ROBOT MOTION PLANNING
    5. GRAPH SEARCH
    6. STATE SPACE APPROACH
    7. BREADTH FIRST SEARCH
    8. DEPTH FIRST SEARCH
    9. A* ALGORITHM
    10. MULTI-NEURON HEURISTIC SEARCH
    11. D* ALGORITHM
    12. EXPERIMENTAL RESULTS
    13. CONCLUSION
  8. Chapter 3: Common Planning Techniques
    1. ABSTRACT
    2. INTRODUCTION
    3. PLANNING USING BELLMAN FORD ALGORITHM
    4. RAPIDLY EXPLORING RANDOM TREES
    5. EMBEDDED SENSOR PLANNING
    6. MORE PLANNING TECHNIQUES
    7. CONCLUSION
  9. Chapter 4: Evolutionary Robotics 1
    1. ABSTRACT
    2. INTRODUCTION
    3. PRINCIPLES OF GENETIC ALGOIRHTM
    4. SIMPLE GENETIC ALGORITHM
    5. CONVERGENCE IN GENETIC ALGORITHM
    6. PATH PLANNING BY GENETIC ALGORITHM
    7. CURVE SMOOTHENING
    8. EVOLUTIONARY STRATEGIES
    9. CONCLUSION
  10. Chapter 5: Evolutionary Robotics 2
    1. ABSTRACT
    2. INTRODUCTION
    3. SWARM INTELLIGENCE
    4. SWARM INTELLIGENCE IN PATH PLANNING
    5. GENETIC PROGRAMMING
    6. GRAMMATICAL EVOLUTION
    7. PATH PLANNING BY GENETIC PROGRAMMING
    8. CONCLUSION
  11. Chapter 6: Behavioral Path Planning
    1. ABSTRACT
    2. INTRODUCTION
    3. FUZZY CONCEPTS
    4. FUZZY OPERATORS
    5. FUZZY INFERENCE SYSTEMS
    6. MOTION PLANNING BY FUZZY INFERENCE SYSTEM
    7. NEURAL NETWORKS
    8. PATH PLANNING USING NEURAL NETWORKS
    9. PATH PLANNING USING NEURAL DYNAMICS
    10. CONCLUSION
  12. Chapter 7: Hybrid Graph-Based Methods
    1. ABSTRACT
    2. INTRODUCTION
    3. HIERARCHICAL MNHS ALGORITHM
    4. THE HIERARCHICAL APPROACH
    5. PROBABILITY-BASED FITNESS
    6. SIMULATION AND RESULTS
    7. HYBRID MNHS AND EVOLUTIONARY ALGORITHMS
    8. RELATION BETWEEN EA AND MNHS
    9. RESULTS
    10. CONCLUSION
  13. Chapter 8: Hybrid Evolutionary Methods
    1. ABSTRACT
    2. INTRODUCTION
    3. EVOLUTIONARY ALGORITHM WITH MOMENTUM
    4. MOMENTUM
    5. EVOLUTIONARY ALGORITHM
    6. VARIABLE GENETIC PARAMETERS
    7. RESULTS
    8. HGAPSO WITH MOMENTUM
    9. RESULTS
    10. HIERARCHICAL EVOLUTIONARY ALGORITHM: HIERARCHY 1
    11. HIERARCHICAL EVOLUTIONARY ALGORITHM: HIERARCHY 2
    12. RESULTS
    13. CONCLUSION
  14. Chapter 9: Hybrid Behavioral Methods
    1. ABSTRACT
    2. INTRODUCTION
    3. FUSION OF A* AND FUZZY PLANNER
    4. SIMULATION AND RESULTS
    5. EVOLVING ROBOTIC PATH
    6. SIMULATIONS AND RESULTS
    7. PLANNING BY ACCELERATED NODES
    8. CONCLUSION
  15. Chapter 10: Multi-Robot Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. PLANNING PROBLEMS IN ROBOTICS
    4. MULTI-ROBOT SYSTEMS
    5. PROBLEMS IN MULTI-ROBOTIC SYSTEMS
    6. MULTI ROBOT PATH PLANNING
    7. APPROACHES
    8. CONCLUSION
  16. Chapter 11: Conclusion
    1. ABSTRACT
    2. CONCLUDING REMARKS
  17. Compilation of References
  18. About the Authors