The synthesis of digital machines with provable epistemic properties
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
In defense of reaction plans as caches
AI Magazine
Situationally driven local navigation for mobile robots
Situationally driven local navigation for mobile robots
Artificial Intelligence
Reliable goal-directed reactive control of autonomous mobile robots
Reliable goal-directed reactive control of autonomous mobile robots
Adaptive execution in complex dynamic worlds
Adaptive execution in complex dynamic worlds
Integrating reaction plans and layered competences through synchronous control
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Find-and-Fetch Search on a Tree
Operations Research
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This paper describes the results of using a reactive control software architecture for a mobile robot retrieval task in an outdoor environment. The software architecture draws from the ideas of universal plans and subsumption's layered control, producing reaction plans that exploit low-level competences as operators. The retrieval task requires the robot to locate and navigate to a donor agent, receive an object from the donor, and return. The implementation employs the concept of navigation templates (NaTs) to construct and update an obstacle space from which navigation plans are developed and continually revised. Selective perception is employed among an infrared beacon detector which determines the bearing to the donor, a real-time stereo vision system which obtains the range, and ultrasonic sensors which monitor for obstacles en route. The perception routines achieve a robust, controlled switching among sensor modes as defined by the reaction plan of the robot. In demonstration runs in an outdoor parking lot, the robot located the donor object while avoiding obstacles and executed the retrieval task among a variety of moving and stationary objects, including moving cars, without stopping its traversal motion. The architecture was previously reported to be effective for simple navigation and pick and place tasks using ultrasonics. Thus, the results reported herein indicate that the architecture will scale well to more complex tasks using a variety of sensors.