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Features

Presents new ideas for gradually enhancing vehicle autonomy in complex environments
Gives an overview of the main achievements and challenges involving autonomous vehicles
Explains the design of innovative multi-controller architectures and their different components
Covers several elementary components related to task modeling, planning, and control that can be used as case studies in courses on robotics, automatic control, or computer science
Addresses mono- and multi-robot navigation
Includes extensive simulations and experiments to illustrate the methodology
Highlights software technologies and algorithms for experiments, with MATLAB and Simulink code available on the author's website
Summary

Improve the Safety, Flexibility, and Reliability of Autonomous Navigation in Complex Environments

Autonomous Vehicle Navigation: From Behavioral to Hybrid Multi-Controller Architectures explores the use of multi-controller architectures in fully autonomous robot navigation-even in highly dynamic and cluttered environments. Accessible to researchers and graduate students involved in mobile robotics and fully autonomous vehicle navigation, the book presents novel techniques and concepts that address different complex mobile robot tasks.

The author examines the development of reliable elementary controllers and proposes mechanisms to manage the interaction of these multi-controller architectures while addressing different constraints and enhancing metrics/criteria linked to the safety, flexibility, and reliability of the proposed control architectures. He covers the modeling of subtasks, reliable obstacle avoidance, appropriate stable control laws for target reaching/tracking, short- and long-term trajectory/waypoint planning, navigation through sequential waypoints, and the cooperative control and interaction of a group of mobile robots. The author's website provides MATLAB® and Simulink® source code of the main procedures related to the task modeling, planning, and control of mobile robots. It also includes videos showing the main simulations and experiments given in the text.

In addition to flexible and bottom-up construction, multi-controller architectures can be formally analyzed to achieve reliable navigation in complex environments. This book reveals innovative control architectures that can lead to fully autonomous vehicle navigation in these challenging situations.



Table of Contents

Global concepts/challenges related to the control of intelligent mobile robots
AUTONOMOUS/INTELLIGENT MOBILE ROBOTS
OVERVIEW OF THE CHALLENGES RELATED TO FULLY AUTONOMOUS NAVIGATION
MAIN BACKGROUNDS AND PARADIGMS
FROM BEHAVIORAL TO MULTI-CONTROLLER ARCHITECTURES
NAVIGATION BASED ON TRAJECTORY OR TARGET SET-POINTS
CONCLUSION

Autonomous navigation in cluttered environments
OVERALL NAVIGATION FRAMEWORK DEFINITION
SAFE OBSTACLE AVOIDANCE AS AN IMPORTANT COMPONENT FOR AUTONOMOUS NAVIGATION
OBSTACLE AVOIDANCE BASED ON PARALLEL ELLIPTIC LIMIT-CYCLE (PELC)
HOMOGENEOUS SET-POINTS DEFINITION FOR ROBOT'S NAVIGATION SUB-TASKS
MULTI-CONTROLLER ARCHITECTURES FOR FULLY REACTIVE NAVIGATION
CONCLUSION

HybridCD (continuous/discrete) multi-controller architectures
INTRODUCTION
ELEMENTARY STABLE CONTROLLERS FOR TARGETS REACHING/TRACKING
PROPOSED HYBRIDCD CONTROL ARCHITECTURES
CONCLUSION

HybridRC (reactive/cognitive) and homogeneous control architecture based on PELC
HYBRIDRC CONTROL ARCHITECTURES
OVERVIEW OF DEVELOPED PLANNING METHODS
OPTIMAL PATH GENERATION BASED ON PELC
HOMOGENEOUS AND HYBRIDRC CONTROL ARCHITECTURE
CONCLUSION

Flexible and reliable autonomous vehicle navigation using optimal waypoint configuration
MOTIVATIONS AND PROBLEM STATEMENT
STRATEGY OF NAVIGATION BASED ON SEQUENTIAL TARGET REACHING
CONTROL ASPECTS
WAYPOINT CONFIGURATION ASPECTS
EXPERIMENTAL VALIDATIONS
CONCLUSION

Cooperative control of multi-robot systems
INTRODUCTION
OVERVIEW OF ADDRESSED MULTI-ROBOT SYSTEMS/TASKS
DYNAMIC MULTI-ROBOT NAVIGATION IN FORMATION
CONCLUSION

General conclusion and prospects
GENERAL CONCLUSION
PROSPECTS

Appendix A: Simulation and experimental platforms
Appendix B: Stability in the sense of Lyapunov