2024 |
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ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation
Abrar Anwar*, John Welsh, Joydeep Biswas, Soha Pouya, Yan Chang
The space of language commands a robot can execute grows combinatorially with scene complexity. Evaluating a robot on this large domain is impractical + takes time, so we introduce contrast sets for robots to make small perturbations to test instances. This leads to good test set estimation and less experimenter effort.
Preprint, 2024
arxiv
code
website
blog
twitter
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Contrast Sets for Evaluating Language-Guided Robot Policies
Abrar Anwar*, Rohan Gupta*, Jesse Thomason
The space of language commands a robot can execute grows combinatorially with scene complexity. Evaluating a robot on this large domain is impractical + takes time, so we introduce contrast sets for robots to make small perturbations to test instances. This leads to good test set estimation and less experimenter effort.
CoRL, 2024
arxiv
twitter
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Which One? Leveraging Context Between Objects and Multiple Views for Language Grounding
Chancharik Mitra*, Abrar Anwar*, Rodolfo Corona, Dan Klein, Trevor Darrell, Jesse Thomason
We present the MAGiC model which selects an object referent based on language meant to distinguish between two similar objects by reasoning over both objects from multiple vantage points.
NAACL, 2024
arxiv
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Generating Contextually-Relevant Navigation Instructions for Blind and Low Vision People
Zain Merchant, Abrar Anwar, Emily Wang, Souti Chattopadhyay, Jesse Thomason
Navigating unfamiliar environments presents significant challenges for blind and low-vision (BLV) individuals. We investigate how grounded instruction generation methods can provide contextually-relevant navigational guidance to BLV users.
ROMAN 2024 Late Breaking Report (LBR) ROMAN 2024 Interactive AI Workshop (Best paper), 2024
arxiv
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Feel the Bite: Robot-Assisted Inside-Mouth Bite Transfer using Robust Mouth Perception and Physical Interaction-Aware Control
Rajat Jenamani, Daniel Stabile, Ziang Liu, Abrar Anwar, Katherine Dimitropoulou, Tapomayukh Bhattacharjee
We design a system to feed people with disabilities in their mouth using real-time mouth perception and tactile-informed control.
HRI. (Best paper nominee), 2024
arxiv
video
website
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2023 |
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Exploring Strategies for Efficient VLN Evaluation
Abrar Anwar*, Rohan Gupta*, Elle Szabo, Jesse Thomason
Evaluation in the real world is often time-consuming and expensive, so we propose a targeted contrast set-based evaluation strategy to efficiently evaluate the linguistic and visual capabilities of an end-to-end VLN policy.
Workshop on Language and Robot Learning (LangRob) @ CoRL. (Oral Presentation), 2023
paper
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2022 |
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Human-Robot Commensality: Bite Timing Prediction for Robot-Assisted Feeding in Groups
Jan Ondras*, Abrar Anwar*, Tong Wu*, Fanjun Bu, Malte Jung, Jorge Jose Ortiz, Tapomayukh Bhattacharjee
We develop data-driven models to predict when a robot should feed during social dining scenarios.
We build a dataset of human-human commensality, develop novel models to learn social dynamics of when to feed, and conduct a human-robot commensality study.
CoRL, 2022
paper
arxiv
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2021 |
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Deep Reinforcement Learning for Optimal Refinement of Cross-Sectional Mesh Sequence Finite Elements
Abrar Anwar
Developed the first deep reinforcement learning framework for mesh refinement and refined âgoodâ quality surface reconstructions of cross-sectional contours using soft-actor critic
Honors Thesis, 2021
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Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation
Blake Holman, Abrar Anwar, Akash Singh, Mauricio Tec, Justin Hart, Peter Stone
We leverage virtual reality to collect gaze and position data to create a predictive model and a mixed effects model to show gaze orientation precedes other features
ICRA, 2021
paper
video
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2020 |
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Evolving Spiking Circuit Motifs using Weight Agnostic Neural Networks.
Abrar Anwar, Craig Vineyard, William Severa, Srideep Musuvathy, Suma Cardwell
An evolutionary, weight agnostic method is used to generate spiking neural networks used for classification, control, and various other tasks
AAAI-21 Undergraduate Consortium , 2021 Computer Science Research Institute Summer Proceedings, 2020 International Conference on Neuromorphic Systems (poster), 2020
paper
tech report
poster
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2019 |
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BrainSLAM: Robust autonomous navigation in sensor-deprived contexts
Felix Wang, James B. Aimone, Abrar Anwar, Srideep Musuvathy.
We explore using brain-inspired approaches to navigation and localization in a noisy, data-sparse environment for a hypersonic glide vehicle. Rotation invariant feature representations are used to increase accuracy and reduce map storage
Sandia National Labs Technical Report, 2019
tech report
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