Peter Amorese

Papers

Total Citations

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About

Peter Amorese is an emerging researcher working at the intersection of autonomous robotics, artificial intelligence planning, and planetary exploration. His work focuses on developing sophisticated decision-making frameworks that enable robots to operate independently in complex, dynamic environments — a challenge with profound implications for both terrestrial and deep-space applications. Among his most notable contributions is his research on cost-preference trade-off planning, where he addresses the fundamental tension between optimal task execution and preferred behavioral strategies for robots managing multiple temporal objectives. This nuanced approach pushes beyond conventional optimization methods to incorporate human-like reasoning about task priorities. Equally compelling is his work on autonomous science planning for planetary missions, particularly targeting distant ocean worlds like Europa and Enceladus, where communication delays make human-in-the-loop operations impractical. His REASON-RECOURSE software framework represents a concrete step toward deploying truly autonomous robotic landers capable of independent scientific discovery. Though early in his career — with his most-cited works accumulating citations of 3 and 2 respectively since 2022-2023 — Amorese is tackling research questions of growing urgency as space agencies worldwide accelerate plans for ambitious robotic exploration missions beyond Mars.