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Andrew D Wilson

6 accepted papers

2025

Grounding Task Assistance with Multimodal Cues from a Single Demonstration

ACL 2025finding

A person’s demonstration often serves as a key reference for others learning the same task. However, RGB video, the dominant medium for representing these demonstrations, often fails to capture fine-grained contextual cues such as intent, safety-critical environmental factors, and subtle preferences…

Cited by 0SourcePDFScholar
2025

Out of Sight, Not Out of Context? Egocentric Spatial Reasoning in VLMs Across Disjoint Frames

EMNLP 2025

An embodied AI assistant operating on egocentric video must integrate spatial cues across time - for instance, determining where an object A, glimpsed a few moments ago lies relative to an object B encountered later. We introduce Disjoint-3DQA , a generative QA benchmark that evaluates this ability

Cited by 0SourcePDFScholar
2021

Decoding Music Attention from "EEG Headphones": A User-Friendly Auditory Brain-Computer Interface

ICASSP 2021accepted

People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device…

Cited by 0SourceScholar
2016

Model-Based Reactive Control for Hybrid and High-Dimensional Robotic Systems

RA-L 2016

Sequential action control (SAC) is a recently developed algorithm for optimal control of nonlinear systems. Previous work by the authors demonstrates that SAC performs well on several benchmark control problems. This work demonstrates applicability of SAC to a variety of robotic systems; we show tha

Cited by 13SourceScholar
2015

Maximizing fisher information using discrete mechanics and projection-based trajectory optimization

ICRA 2015poster

This paper reformulates an optimization algorithm previously presented in continuous-time to one using structured integration and structured linearization methods from discrete mechanics. The objective is to synthesize trajectories for dynamic robotic systems that improve the estimation of model par…

Cited by 6SourceScholar
2015

Real-time trajectory synthesis for information maximization using Sequential Action Control and least-squares estimation

IROS 2015poster

This paper presents the details and experimental results from an implementation of real-time trajectory generation and parameter estimation of a dynamic model using the Baxter Research Robot from Rethink Robotics. Trajectory generation is based on the maximization of Fisher information in real-time…

Cited by 30SourceScholar