9 citations · 14 across the 15 of their papers we have counts for
16 papers
STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction
Nathan Tsoi, Michael J. Munje, Tejas Oberoi +5
Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…
AAAI-26 Dual Submissions: Novel Challenges
Kiri L. Wagstaff, Joydeep Biswas, Erich Merrill +4
Dual submissions, in which identical or substantially similar papers are simultaneously submitted to one or more archival venues, without cross-citation or disclosure, are a growin…
VOFA: Visual Object Goal Pushing with Force-Adaptive Control for Humanoids
Zichao Hu, Zifan Xu, Dongsik Chang +6
The ability to push large objects in a goal-directed manner using onboard egocentric perception is an essential skill for humanoid robots to perform complex tasks such as material…
AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot
Joydeep Biswas, Sheila Schoepp, Gautham Vasan +10
Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances i…
Learning Agile Striker Skills for Humanoid Soccer Robots from Noisy Sensory Input
Zifan Xu, Myoungkyu Seo, Dongmyeong Lee +8
Learning fast and robust ball-kicking skills is a critical capability for humanoid soccer robots, yet it remains a challenging problem due to the need for rapid leg swings, postura…
The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All
Zifan Xu, Kristen Procko, Michael Munje +4
In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, whi…
Searching in Space and Time: Unified Memory-Action Loops for Open-World Object Retrieval
Taijing Chen, Sateesh Kumar, Junhong Xu +3
Service robots must retrieve objects in dynamic, open-world settings where requests may reference attributes ("the red mug"), spatial context ("the mug on the table"), or past stat…
Terrain Costmap Generation via Scaled Preference Conditioning
Luisa Mao, Garrett Warnell, Peter Stone +1
Successful autonomous robot navigation in off-road domains requires the ability to generate high-quality terrain costmaps that are able to both generalize well over a wide variety…
ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion
Zichao Hu, Chen Tang, Michael J. Munje +6
This paper considers the problem of enabling robots to navigate dynamic environments while following instructions. The challenge lies in the combinatorial nature of instruction spe…
SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation
Michael J. Munje, Chen Tang, Shuijing Liu +6
Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…
The Essentials of AI for Life and Society: An AI Literacy Course for the University Community
Joydeep Biswas, Don Fussell, Peter Stone +4
We describe the development of a one-credit course to promote AI literacy at The University of Texas at Austin. In response to a call for the rapid deployment of class to serve a b…
HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments
Shuijing Liu, Haochen Xia, Fatemeh Cheraghi Pouria +5
We study the problem of robot navigation in dense and interactive crowds with static constraints such as corridors and furniture. Previous methods fail to consider all types of spa…
SPOT: SE(3) Pose Trajectory Diffusion for Object-Centric Manipulation
Cheng-Chun Hsu, Bowen Wen, Jie Xu +5
We introduce SPOT, an object-centric imitation learning framework. The key idea is to capture each task by an object-centric representation, specifically the SE(3) object pose traj…
PACER: Preference-conditioned All-terrain Costmap Generation
Luisa Mao, Garrett Warnell, Peter Stone +1
In autonomous robot navigation, terrain cost assignment is typically performed using a semantics-based paradigm in which terrain is first labeled using a pre-trained semantic class…
KinScene: Model-Based Mobile Manipulation of Articulated Scenes
Cheng-Chun Hsu, Ben Abbatematteo, Zhenyu Jiang +3
Sequentially interacting with articulated objects is crucial for a mobile manipulator to operate effectively in everyday environments. To enable long-horizon tasks involving articu…
Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds
Rohan Chandra, Haresh Karnan, Negar Mehr +2
Social robot navigation in crowded public spaces such as university campuses, restaurants, grocery stores, and hospitals, is an increasingly important area of research. One of the…