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Enhanced Decision-making with Autonomous Agents in Air, Surface, and Sub-surface Environment

Explore the impacts and challenges of aided and unaided decision-making processes with diverse agent types in different environments. Discover how joint performance and human factors influence the acceptance of imperfect agents. Step into the simulation of Orange Arena to tackle visual limitations and obstacle navigation.

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Enhanced Decision-making with Autonomous Agents in Air, Surface, and Sub-surface Environment

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Presentation Transcript

  1. Tandem Trust & Error • The sub/surface/air type decision is aided • One of three levels of agent autonomy may be present • Errors of various types may be present

  2. Aided Decision Agent type &Error affected Air/surface/sub typing decision

  3. Unaided Decision Agent type aloneaffected unaided portions of the task

  4. Conclusions • Joint performance was key • Users were prepared to accept even imperfect agents as peers when their contribution improved overall performance

  5. Simulation of Orange Arena

  6. Human Factors Challenges • World through a straw (restricted FOV) • Camera control for search/navigation (Hughes & Lewis, HFES 2002) • Survey knowledge (mapping environment) from restricted FOV & impeded movement • Visual “smearing” from close surfaces • unfamiliar ground level perspective • Difficult distance judgments from degraded 2D image • Difficult orientation judgments from visual cues in disorderly environment • Difficult locomotion due to out-of-view & negative obstacles

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