{"627123":{"#nid":"627123","#data":{"type":"event","title":"Andrew Price Thesis Defense","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ECommittee Members:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProfessor Henrik Christensen (Advisor), ECE \u0026amp; UCSD\u003C\/p\u003E\r\n\r\n\u003Cp\u003EStephen Balakirsky, PhD - GTRI\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProfessor Patricio Vela - ECE\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProfessor Aaron Ames - CalTech\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProfessor Dmitry Berenson - University of Michigan\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis document introduces a novel technique for addressing the fragility of solutions that is common to configuration space-based planners. Both the state and the pre- and post-conditions of actions are represented as volumes of the configuration space. Feasibility of the various action types is determined by a subset test: if the set of possible states is a subset of the pre-condition set of a given action, then that action is feasible. This system is then incorporated into a planning system which is demonstrated on a number of household, scientific, and industrial application domains.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the development of this framework, we build off of the idea of affordances: a high-level technique for reasoning about the space of latent action possibilities between an agent and its environment. In the language of affordances, our contributions are as follows:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E* We formalize the computational notion of an affordance by introducing a set-based formulation of action pre-conditions and post-conditions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E* We define the feasibility of an action as an inclusion predicate between convex sets representing the possible system configuration and the parameterized action pre-conditions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E* We introduce a novel planning algorithm incorporating the previous contributions to jointly reason over information gathering and state transformation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E* We demonstrate the proposed system on a variety of simulated and real scenarios derived from household, scientific research, and industrial application domains.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis approach has a number of indirect benefits as well. First, the definition of action predicate sets depends on deep knowledge of the agent in question; as a result, the affordance representation specializes to a variety of agents while requiring only commonly-used mechanical and kinematic parameters. Second, as actions may serve to expand or contract the belief state, information-gathering actions may be planned without the need for e.g. a bespoke entropy minimization framework.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThese benefits do incur some trade-offs, however. An explicit enumeration of possible actions is required, as are detailed models of their input-output behavior. These models may be developed from existing theory, via simulation, or by physical experimentation. In principle, such models could be discovered by self-experimentation or learning from demonstration, but these techniques are outside the scope of this work.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Set Predicates for Planning with Robot Capabilities and Affordances"}],"uid":"28475","created_gmt":"2019-10-03 20:17:51","changed_gmt":"2019-10-03 20:44:55","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-10-16T15:00:00-04:00","event_time_end":"2019-10-16T17:00:00-04:00","event_time_end_last":"2019-10-16T17:00:00-04:00","gmt_time_start":"2019-10-16 19:00:00","gmt_time_end":"2019-10-16 21:00:00","gmt_time_end_last":"2019-10-16 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}