Rowland O'Flaherty — accepted AI-conference papers

2025

VT-Refine: Learning Bimanual Assembly with Visuo-Tactile Feedback via Simulation Fine-Tuning

Binghao Huang, Jie Xu, Iretiayo Akinola, Wei Yang, Balakumar Sundaralingam, Rowland O'Flaherty +5

CoRL 2025poster

Humans excel at bimanual assembly tasks by adapting to rich tactile feedback—a capability that remains difficult to replicate in robots through behavioral cloning alone, due to the suboptimality and limited diversity of human demonstrations. In this work, we present VT-Refine, a visuo-tactile policy…

Cited by 0 Source ↗code ↗Scholar ↗

2015

Optimal exploration in unknown environments

Rowland O'Flaherty, Magnus Egerstedt

IROS 2015poster

This paper presents an algorithm that optimally explores an unknown environment with regions of varying degrees of importance. The algorithm, termed Ergodic Environmental Exploration (E3), is a finite receding horizon optimal control algorithm that minimizes control effort and the difference between…

Cited by 13 Source ↗Scholar ↗