Organizational Unit:
Mobile Robot Laboratory
Mobile Robot Laboratory
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ItemTowards the Unification of Navigational Planning and Reactive Control(Georgia Institute of Technology, 1989) Arkin, Ronald C.The illusion that reactive and hierarchical planning methods are at odds with each other needs to be dropped. By exploiting each method's strengths, a synthesis of hierarchical and reactive paradigms can yield robust, flexible, and generalizable navigation. Psychological and neuroscientific studies support this claim.
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ItemWorkstation Recognition Using a Constrained Edge Based Hough Transform for Mobile Robot Navigation(Georgia Institute of Technology, 1989) Arkin, Ronald C. ; Vaughn, David L.Landmark recognition is a task required of many robotic systems. In this work, we examine the use of a constrained Hough transform used by a mobile robot to locate a docking workstation. This algorithm deals with the uncertainty inherent in a mobile robot by making use of a spatial uncertainty map maintained by the robot. Several iterations of the Hough transform are run with transformed models of the dock. Votes are accumulated in a collapsed Hough space which, although unable to recover range and orientation information, simplifies locating the dock within the image.
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ItemIntelligent Mobile Robots in the Workplace: Leaving the Guide Behind(Georgia Institute of Technology, 1988) Arkin, Ronald C.Flexible manufacturing systems (FMS) that incorporate transport robots are currently dominated by the use of automatic guided vehicles. These AGVs generally require significant restructuring of the workplace in order for them to be useful. The concept of flexibility in manufacturing is somewhat compromised by this strategy. Our previous work in mobile robots, resulting in the Autonomous Robot Architecture (AuRA), is applied to the manufacturing domain. This approach, contrary to the AGV methodology, embeds significant amounts of knowledge (both environmental and behavioral) to ultimately give a mobile robot far greater latitude in interacting with its environment. This paper presents the motivation and subsequent simulation studies that demonstrate the feasibility of migrating schema-based navigation into an FMS. In particular, the creation of a docking motor schema to accomplish interaction with the workplace is detailed.
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ItemTowards Cosmopolitan Robots: Intelligent Navigation in Extended Man-Made Environments(Georgia Institute of Technology, 1987) Arkin, Ronald C.In the past, mobile robots have been constrained to operate in either an indoor or an outdoor environment, not both. Special purpose representations and ad hoc sensor techniques geared towards tasks of narrow focus have dominated these efforts. It is the purpose of this dissertation to lead towards the development of a more cosmopolitan robot; one whose domain of interaction is not as restricted as these previous attempts. The Autonomous Robot Architecture (AuRA) has been developed to meet these challenges. A "meadow" map, used for global path planning and containing embedded a priori knowledge to guide sensor expectations, serves as the robot's long term memory. A layered short term memory based on instantiated meadows represents the currently perceived world. A hierarchical path planner produces a global path free of collisions with all modeled obstacles. Schema theory is extended to include the mobile robot domain and serves as the principal theoretical framework. The schema-based path execution system handles unexpected and dynamic obstacles not present in the robot's world model. This motor schema-based navigation system produces reactive/reflexive behavior in direct response to sensor events. In addition, new techniques in the treatment of robot uncertainty which expedite sensory processing are presented. These include the use of a spatial error map with associated error growth and reduction techniques. Several computer vision sensor strategies have been developed for use within AuRA. These include a fast line-finding algorithm, a fast region segmentation algorithm, and a depth-from-motion algorithm. Experiments using our mobile vehicle HARV demonstrate the use of these vision algorithms for navigational purposes. Schema-based navigation using ultrasonic sensing is also demonstrated experimentally.