37 citations · 101 across the 38 of their papers we have counts for
30 papers · 1 filter
HapticWorld: an Interactive World Simulator with Real-time Torque Feedback
Shaoting Peng, Litian Liang, Yixuan Wang +4
Contact-rich manipulation depends on force sensing that is hard to infer from visual signals alone, both for collecting demonstrations and for training policies. Force-annotated da…
ARGUS: Aligning Robot Scene Geometry Under Shifting Views with Large 3D Vision Models
Rishik Sathua, Haonan Chen, Katherine Driggs-Campbell
Large-scale visuomotor policies have demonstrated impressive performance across a wide range of robot manipulation tasks. However, despite this success, manipulation polices often…
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors
Pengcheng Wang, Kaiwen Hong, Chensheng Peng +4
Unlike chatbots, physical AI must act while the world keeps evolving. Therefore, the inter-chunk pause of synchronous executors are fatal for dynamic tasks regardless of how fast t…
Tactile-Based Human Intent Recognition for Robot Assistive Navigation
Shaoting Peng, Dakarai Crowder, Wenzhen Yuan +1
Robot assistive navigation (RAN) is critical for enhancing the mobility and independence of the growing population of mobility-impaired individuals. However, existing systems often…
Trust-Aware Embodied Bayesian Persuasion for Mixed-Autonomy
Shaoting Peng, Katherine Driggs-Campbell, Roy Dong
Safe and efficient interaction between autonomous vehicles (AVs) and human-driven vehicles (HVs) is a critical challenge for future transportation systems. While game-theoretic mod…
Multi-Modal Manipulation via Multi-Modal Policy Consensus
Haonan Chen, Jiaming Xu, Hongyu Chen +7
Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation is often suboptimal: dominant modalit…
Characterizing the Robustness of Black-Box LLM Planners Under Perturbed Observations with Adaptive Stress Testing
Neeloy Chakraborty, John Pohovey, Melkior Ornik +1
Large language models (LLMs) have recently demonstrated success in decision-making tasks including planning, control, and prediction, but their tendency to hallucinate unsafe and u…
Do You Know the Way? Human-in-the-Loop Understanding for Fast Traversability Estimation in Mobile Robotics
Andre Schreiber, Katherine Driggs-Campbell
The increasing use of robots in unstructured environments necessitates the development of effective perception and navigation strategies to enable field robots to successfully perf…
Tool-as-Interface: Learning Robot Policies from Observing Human Tool Use
Haonan Chen, Cheng Zhu, Shuijing Liu +2
Tool use is essential for enabling robots to perform complex real-world tasks, but learning such skills requires extensive datasets. While teleoperation is widely used, it is slow,…
Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models
Haonan Chen, Jiaming Xu, Lily Sheng +4
When performing tasks like laundry, humans naturally coordinate both hands to manipulate objects and anticipate how their actions will change the state of the clothes. However, ach…
Towards Uncertainty Unification: A Case Study for Preference Learning
Shaoting Peng, Haonan Chen, Katherine Driggs-Campbell
Learning human preferences is essential for human-robot interaction, as it enables robots to adapt their behaviors to align with human expectations and goals. However, the inherent…
Interaction-aware Conformal Prediction for Crowd Navigation
Zhe Huang, Tianchen Ji, Heling Zhang +3
During crowd navigation, robot motion plan needs to consider human motion uncertainty, and the human motion uncertainty is dependent on the robot motion plan. We introduce Interact…
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…
Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation
Neeloy Chakraborty, Yixiao Fang, Andre Schreiber +6
Teleoperation is an important technology to enable supervisors to control agricultural robots remotely. However, environmental factors in dense crop rows and limitations in network…
Topology-Guided ORCA: Smooth Multi-Agent Motion Planning in Constrained Environments
Fatemeh Cheraghi Pouria, Zhe Huang, Ananya Yammanuru +2
We present Topology-Guided ORCA as an alternative simulator to replace ORCA for planning smooth multi-agent motions in environments with static obstacles. Despite the impressive pe…
Human-Agent Joint Learning for Efficient Robot Manipulation Skill Acquisition
Shengcheng Luo, Quanquan Peng, Jun Lv +4
Employing a teleoperation system for gathering demonstrations offers the potential for more efficient learning of robot manipulation. However, teleoperating a robot arm equipped wi…
W-RIZZ: A Weakly-Supervised Framework for Relative Traversability Estimation in Mobile Robotics
Andre Schreiber, Arun N. Sivakumar, Peter Du +3
Successful deployment of mobile robots in unstructured domains requires an understanding of the environment and terrain to avoid hazardous areas, getting stuck, and colliding with…
Structured Graph Network for Constrained Robot Crowd Navigation with Low Fidelity Simulation
Shuijing Liu, Kaiwen Hong, Neeloy Chakraborty +1
We investigate the feasibility of deploying reinforcement learning (RL) policies for constrained crowd navigation using a low-fidelity simulator. We introduce a representation of t…
An Attentional Recurrent Neural Network for Occlusion-Aware Proactive Anomaly Detection in Field Robot Navigation
Andre Schreiber, Tianchen Ji, D. Livingston McPherson +1
The use of mobile robots in unstructured environments like the agricultural field is becoming increasingly common. The ability for such field robots to proactively identify and avo…
Predicting Object Interactions with Behavior Primitives: An Application in Stowing Tasks
Haonan Chen, Yilong Niu, Kaiwen Hong +4
Stowing, the task of placing objects in cluttered shelves or bins, is a common task in warehouse and manufacturing operations. However, this task is still predominantly carried out…
DRAGON: A Dialogue-Based Robot for Assistive Navigation with Visual Language Grounding
Shuijing Liu, Aamir Hasan, Kaiwen Hong +7
Persons with visual impairments (PwVI) have difficulties understanding and navigating spaces around them. Current wayfinding technologies either focus solely on navigation or provi…
Dynamic-Resolution Model Learning for Object Pile Manipulation
Yixuan Wang, Yunzhu Li, Katherine Driggs-Campbell +2
Dynamics models learned from visual observations have shown to be effective in various robotic manipulation tasks. One of the key questions for learning such dynamics models is wha…
Conveying Autonomous Robot Capabilities through Contrasting Behaviour Summaries
Peter Du, Surya Murthy, Katherine Driggs-Campbell
As advances in artificial intelligence enable increasingly capable learning-based autonomous agents, it becomes more challenging for human observers to efficiently construct a ment…
Adaptive Failure Search Using Critical States from Domain Experts
Peter Du, Katherine Driggs-Campbell
Uncovering potential failure cases is a crucial step in the validation of safety critical systems such as autonomous vehicles. Failure search may be done through logging substantia…