activity
20172026
most citedModel-Based Control Using Koopman Operators

85 citations · 281 across the 21 of their papers we have counts for

collaborators

25 papers

cs.RO2026

Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial

Max Muchen Sun, Cem Bilaloglu, Ananya Rao +6

Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data. Recent advances in diffusion l…

cs.RO2024★ 5 cited

Koopman Operators in Robot Learning

Lu Shi, Masih Haseli, Giorgos Mamakoukas +5

Koopman operator theory offers a rigorous treatment of dynamics and has been emerging as an alternative modeling and learning-based control method across various robotics sub-domai…

cs.RO2023

Bi-Level Image-Guided Ergodic Exploration with Applications to Planetary Rovers

Elena Wittemyer, Ian Abraham

We present a method for image-guided exploration for mobile robotic systems. Our approach extends ergodic exploration methods, a recent exploration approach that prioritizes comple…

cs.RO2023

Time Optimal Ergodic Search

Dayi Dong, Henry Berger, Ian Abraham

Robots with the ability to balance time against the thoroughness of search have the potential to provide time-critical assistance in applications such as search and rescue. Current…

cs.RO2022★ 1 cited

Scale-Invariant Specifications for Human-Swarm Systems

Joel Meyer, Ahalya Prabhakar, Allison Pinosky +9

We present a method for controlling a swarm using its spectral decomposition -- that is, by describing the set of trajectories of a swarm in terms of a spatial distribution through…

cs.RO2022★ 1 cited

Safety-Critical Ergodic Exploration in Cluttered Environments via Control Barrier Functions

Cameron Lerch, Dayi Dong, Ian Abraham

In this paper, we address the problem of safe trajectory planning for autonomous search and exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) t…