Enabling Robust Persistent Autonomy in Robots
Technical Report,01 Jan 2017,31 Dec 2019
Cornell University Ithaca United States
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The long-term objectives of this project are to increase the level of autonomy of robots by giving them an introspective capability. Introspection involves modeling the robots own behavior and using that model to reflect on how to change its behavior in response to unanticipated events. As a part of this project, we have developed predictive models of a number of robot models for testing these algorithms, including an autonomous car, an autonomous airship, a pedestrian robot navigating among people, and a manipulation scenario involving cloth folding. We made use of these models to demonstrate three primary goals failure handling, mission planning, and adaptable specification. Recommendations for future research directions in persistent autonomy are included.