31 citations · 59 across the 13 of their papers we have counts for
9 papers · 1 filter
hint: Hierarchical World Models for Inference-Time Temporal Logic Guidance
Moritz Zoellner, Anastasios Manganaris, Ahmed H. Qureshi +1
A central goal of robot learning is to enable robots to execute rich instructions specified at runtime. Large-scale language-conditioned policies have made substantial progress tow…
Temporal Logic Guidance for Action-Only Diffusion Policies with World Models
Moritz Zoellner, Anastasios Manganaris, Rohan Paleja
Diffusion policies enable multimodal robot behavior but offer limited ability to choose among behavior modes at inference time, even though such control is desirable in human-robot…
Heterogeneous Policy Networks for Composite Robot Team Communication and Coordination
Esmaeil Seraj, Rohan Paleja, Luis Pimentel +7
High-performing human-human teams learn intelligent and efficient communication and coordination strategies to maximize their joint utility. These teams implicitly understand the d…
Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies
Xinchen Jin, Aditya Chatterjee, Pranav Kumar +1
Vision-Language-Action (VLA) policies translate language and visual inputs into robot actions, where their hidden representations directly shape closed-loop behavior. However, mech…
Faster Model Predictive Control via Self-Supervised Initialization Learning
Zhaoxin Li, Xiaoke Wang, Letian Chen +3
Model Predictive Control (MPC) is widely used in robot control by optimizing a sequence of control outputs over a finite-horizon. Computational approaches for MPC include determini…
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems
Rohan Paleja, Michael Munje, Kimberlee Chang +2
Collaborative robots and machine learning-based virtual agents are increasingly entering the human workspace with the aim of increasing productivity and enhancing safety. Despite t…