Howard Coffin — accepted AI-conference papers

2022

A Local Optimization Framework for Multi-Objective Ergodic Search

Zhongqiang Ren, Akshaya Kesarimangalam Srinivasan, Howard Coffin, Ian Abraham, Howie Choset

RSS 2022poster

Robots have the potential to perform search for a variety of applications under different scenarios. Our work is motivated by humanitarian assistant and disaster relief (HADR) where often it is critical to find signs of life in the presence of conflicting criteria, objectives, and information. We be…

Cited by 8 Source ↗PDF ↗code ↗Scholar ↗

2022

Multi-Agent Dynamic Ergodic Search with Low-Information Sensors

Howard Coffin, Ian Abraham, Guillaume Sartoretti, Tyler Dillstrom, Howie Choset

ICRA 2022poster

The long-term goal of this work is to enable agents with low-information sensors to perform tasks usually restricted to ones with more sophisticated, high-information sensing capabilities. Our approach is to regulate the motion of these low-information agents to obtain “high-information” results. As…

Cited by 18 Source ↗Scholar ↗