Integration of reactive behaviors and enhanced topological map for robust mobile robot navigation

A navigation system for an autonomous mobile robot working in indoor environments is presented. The system takes advantage of the deliberative (plan-based) approach and the reactive (behavior-based) approach. In the reactive part of the system are local behaviors that are independent, action-generating entities. We also provide higher-level deliberative modules that make interactions manageable so the system can accomplish more meaningful tasks. The deliberative modules control the activation and deactivation of individual local behaviors based on current situations, representing the position of the robot and the path to the goal. The situation is determined by a mapping subsystem consisting of an enhanced topological map, a localization module and a planning module. The use of the explicit world model, especially in a topological manner, makes it possible to reliably localize the robot and plan an efficient path. The paper also provides a detailed description of a localization module based on dead reckoning, and a planning module that selects an efficient and reliable path.

[1]  Hyun Seung Yang,et al.  CAIR-2 Intelligent Mobile Robot for Guidance and Delivery , 1996, AI Mag..

[2]  Avinash C. Kak,et al.  Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties , 1992, CVGIP Image Underst..

[3]  Illah R. Nourbakhsh,et al.  DERVISH - An Office-Navigating Robot , 1995, AI Mag..

[4]  Leonard P. Wesley Autonomous locative reasoning: an evidential approach , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[5]  Tod S. Levitt,et al.  Qualitative Navigation for Mobile Robots , 1990, Artif. Intell..

[6]  David Kortenkamp,et al.  Cognitive maps for mobile robots: A representation for mapping and navigation , 1993 .

[7]  Viii Supervisor Sonar-Based Real-World Mapping and Navigation , 2001 .

[8]  Yoram Koren,et al.  The vector field histogram-fast obstacle avoidance for mobile robots , 1991, IEEE Trans. Robotics Autom..

[9]  Olivier D. Faugeras,et al.  Maintaining representations of the environment of a mobile robot , 1988, IEEE Trans. Robotics Autom..

[10]  David Kortenkamp,et al.  Topological Mapping for Mobile Robots Using a Combination of Sonar and Vision Sensing , 1994, AAAI.

[11]  Alessandro Saffiotti Some Notes on the Integration of Planning and Reactivity in Autonomous Mobile Robots , 1993 .

[12]  Benjamin Kuipers,et al.  A Robust, Qualitative Method for Robot Spatial Learning , 1988, AAAI.

[13]  Reid G. Simmons,et al.  Structured control for autonomous robots , 1994, IEEE Trans. Robotics Autom..

[14]  Maja J. Mataric,et al.  Integration of representation into goal-driven behavior-based robots , 1992, IEEE Trans. Robotics Autom..

[15]  Ronald C. Arkin,et al.  Motor schema based navigation for a mobile robot: An approach to programming by behavior , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[16]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[17]  Ingemar J. Cox,et al.  Dynamic Map Building for an Autonomous Mobile Robot , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[18]  Hyun Seung Yang,et al.  Integrated control architecture based on behavior and plan for mobile robot navigation , 1998, Robotica.

[19]  Yoram Koren,et al.  Potential field methods and their inherent limitations for mobile robot navigation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[20]  David W. Payton,et al.  Plan guided reaction , 1990, IEEE Trans. Syst. Man Cybern..

[21]  Ronald C. Arkin,et al.  Integrating behavioral, perceptual, and world knowledge in reactive navigation , 1990, Robotics Auton. Syst..

[22]  Avinash C. Kak,et al.  Fast Vision-guided Mobile Robot Navigation Using Model-based Reasoning And Prediction Of Uncertainties , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.