Autonomous vehicle navigation: from behavioral to hybrid multi-controller architectures

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 ARCHITECTURESNAVIGATION BASED ON TRAJECTORY OR TARGET SET-POINTS CONCLUSION Autonomous navigation in cluttered environmentsOVERALL 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 METHODSOPTIMAL PATH GENERATION BASED ON PELC HOMOGENEOUS AND HYBRIDRC CONTROL ARCHITECTURECONCLUSION Flexible and reliable autonomous vehicle navigation using optimal waypoint configurationMOTIVATIONS 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 FORMATIONCONCLUSION General conclusion and prospects GENERAL CONCLUSION PROSPECTS Appendix A: Simulation and experimental platforms Appendix B: Stability in the sense of Lyapunov