The virtual wall approach to limit cycle avoidance for unmanned ground vehicles

Authors:
Camilo Ordonez;Emmanuel G. Collins, Jr.;Majura F. Selekwa;Damion D. Dunlap
Affiliations:
Center for Intelligent Systems, Control and Robotics (CISCOR), Department of Mechanical Engineering, Florida A&M University - Florida State University College of Engineering, Tallahassee, FL 32310 ...;Center for Intelligent Systems, Control and Robotics (CISCOR), Department of Mechanical Engineering, Florida A&M University - Florida State University College of Engineering, Tallahassee, FL 32310 ...;Department of Mechanical Engineering and Applied Mechanics, North Dakota State University, Fargo, ND 58105, United States;Center for Intelligent Systems, Control and Robotics (CISCOR), Department of Mechanical Engineering, Florida A&M University - Florida State University College of Engineering, Tallahassee, FL 32310 ...
Venue:
Robotics and Autonomous Systems
Year:
2008

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Abstract

Robot Navigation in unknown and very cluttered environments constitutes one of the key challenges in unmanned ground vehicle (UGV) applications. Navigational limit cycles can occur when navigating (UGVs) using behavior-based or other reactive algorithms. Limit cycles occur when the robot is navigating towards the goal but enters an enclosure that has its opening in a direction opposite to the goal. The robot then becomes effectively trapped in the enclosure. This paper presents a solution named the Virtual Wall Approach (VWA) to the limit cycle problem for robot navigation in very cluttered environments. This algorithm is composed of three stages: detection, retraction, and avoidance. The detection stage uses spatial memory to identify the limit cycle. Once the limit cycle has been identified, a labeling operator is applied to a local map of the obstacle field to identify the obstacle or group of obstacles that are causing the deadlock enclosure. The retraction stage defines a waypoint for the robot outside the deadlock area. When the robot crosses the boundary of the deadlock enclosure, a virtual wall is placed near the endpoints of the enclosure to designate this area as off-limits. Finally, the robot activates a virtual sensor so that it can proceed to its original goal, avoiding the virtual wall and obstacles found on its way. Simulations, experiments, and analysis of the VWA implemented on top of a preference-based fuzzy behavior system demonstrate the effectiveness of the proposed method.