{"663209":{"#nid":"663209","#data":{"type":"event","title":"PhD Defense by Andrew Messing","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EInterleaving Allocation, Planning, and Scheduling for Heterogeneous Multi-Robot Coordination through Shared Constraints\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate: \u003C\/strong\u003ETuesday, November 29\u003Csup\u003Eth\u003C\/sup\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E12 pm\u0026nbsp;- 2 pm EST\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation: \u003C\/strong\u003E(in person) Klaus 1315, (virtual) Link will be sent closer to the date\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Seth Hutchinson (Advisor) - School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Sonia Chernova\u0026nbsp;- School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Harish Ravichandar\u0026nbsp;- School of Interactive Computing, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Nicholas Roy - Department of Aeronautics and Astronautics, Massachusetts Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Alekandra Faust - Senior Staff Research Scientist, Google Brain Research\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn a wide variety of domains, such as warehouse automation, agriculture, defense, and assembly, effective coordination of heterogeneous multi-robot teams is needed to solve complex problems. Effective coordination is predicated on the ability to solve the four fundamentally intertwined questions of coordination: \u003Cem\u003Ewhat \u003C\/em\u003E(task planning), \u003Cem\u003Ewho \u003C\/em\u003E(task allocation), \u003Cem\u003Ewhen \u003C\/em\u003E(scheduling), and \u003Cem\u003Ehow \u003C\/em\u003E(motion planning). Owing to the complexity of these four questions and their interactions, existing approaches to multi-robot coordination have resorted to defining and solving problems that focus on a subset of the four questions. Notable examples include Task and Motion Planning (\u003Cem\u003Ewhat \u003C\/em\u003Eand \u003Cem\u003Ehow\u003C\/em\u003E), Multi-Agent Planning (\u003Cem\u003Ewhat \u003C\/em\u003Eand \u003Cem\u003Ewho\u003C\/em\u003E), and Multi-Agent Path Finding (\u003Cem\u003Ewho \u003C\/em\u003Eand \u003Cem\u003Ehow\u003C\/em\u003E). In fact, a holistic problem formulation that fully integrates the four questions lies beyond the scope of prior literature.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis dissertation focuses on \u003Cstrong\u003Eexamining the use of shared constraints on tasks and robots to interleave algorithms for task planning, task allocation, scheduling, and motion planning and investigating the hypothesis that a framework that interleaves algorithms to these four sub-problems will lead to solutions with lower makespans, greater computational efficiency, and the ability to solve larger problems\u003C\/strong\u003E. To support this claim, this dissertation contributes: (\u003Cem\u003Ei\u003C\/em\u003E) a novel temporal planner that interleaves task planning and scheduling layers, (\u003Cem\u003Eii\u003C\/em\u003E) a trait-based time-extended task allocation framework that interleaves task allocation, scheduling, and motion planning, (\u003Cem\u003Eiii\u003C\/em\u003E) the formulation of holistic heterogeneous multi-robot coordination problem that simultaneously considers all four questions, (\u003Cem\u003Eiv\u003C\/em\u003E) a framework that interleaves layers for all four questions to solve this holistic heterogeneous multi-robot coordination problem, (\u003Cem\u003Ev\u003C\/em\u003E) a scheduling algorithm that reasons about temporal uncertainty, provides a theoretical guarantee on risk, and can be utilized within our framework, and (\u003Cem\u003Evi\u003C\/em\u003E) a learning-based scheduling algorithm that reasons about deadlines and can be utilized within our framework.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Interleaving Allocation, Planning, and Scheduling for Heterogeneous Multi-Robot Coordination through Shared Constraints"}],"uid":"27707","created_gmt":"2022-11-15 22:06:58","changed_gmt":"2022-11-15 22:06:58","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-29T12:00:00-05:00","event_time_end":"2022-11-29T14:03:00-05:00","event_time_end_last":"2022-11-29T14:03:00-05:00","gmt_time_start":"2022-11-29 17:00:00","gmt_time_end":"2022-11-29 19:03:00","gmt_time_end_last":"2022-11-29 19:03:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}