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AI and Robotics Wheeler Ruml Department of Computer Science - - PowerPoint PPT Presentation
AI and Robotics Wheeler Ruml Department of Computer Science - - PowerPoint PPT Presentation
AI and Robotics Wheeler Ruml Department of Computer Science www.cs.unh.edu/~ruml Wheeler Ruml (UNH) AI and Robotics 1 / 5 Research Planning: ideas from combinatorial search Research Integration canon (Robin): models (abstraction)
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Research
■ Research ■ Integration ■ Challenges
Wheeler Ruml (UNH) AI and Robotics – 2 / 5
Planning: ideas from combinatorial search
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canon (Robin): models (abstraction) + inference (search)
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abstraction-based guidance
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suboptimal search (bounded, contract, utility-based)
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real-time planning, concurrent execution (Manuela)
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multi-level planning (Max, Dawn): hierarchical search Perception:
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focus of attention, ‘purposeful’ (Jana, Manuela, Matthias)
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Encouraging Integration
■ Research ■ Integration ■ Challenges
Wheeler Ruml (UNH) AI and Robotics – 3 / 5
Funders:
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fund workshop invited speakers
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fund presentation of journal papers at related conferences
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fund workshops that rotate among conferences
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fund summer school or workshop (Robin)
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how to encourage publishing in diverse venues?
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Encouraging Integration
■ Research ■ Integration ■ Challenges
Wheeler Ruml (UNH) AI and Robotics – 3 / 5
Funders:
■
fund workshop invited speakers
■
fund presentation of journal papers at related conferences
■
fund workshops that rotate among conferences
■
fund summer school or workshop (Robin)
■
how to encourage publishing in diverse venues? Event organizers:
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umbrella model: present best papers from related conferences, ‘what’s hot’ talks
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clearly demarcate outreach from research events, invite
- rganizers to report out on current technical approaches and
challenges
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( not co-location: too hard )
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Challenge Problems
■ Research ■ Integration ■ Challenges
Wheeler Ruml (UNH) AI and Robotics – 4 / 5
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cheap reliable common platform (UBR-1)
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works in simulation
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min ∆ ‘shaping’. eg: Physical TSP, setting the table
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ask people with jobs, money, cool factor (≈ David E. Smith)
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counter-balance with explicit encouragement of exploratory research on new problem settings (Tomas)
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