activity
20202025
most citedMulti-Modal Anomaly Detection for Unstructured and Uncertain Environments

13 citations · 29 across the 9 of their papers we have counts for

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9 papers · 1 filter

cs.RO2025

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…

cs.RO2025

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…

cs.RO2024

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…

cs.RO2023

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…

cs.RO2023★ 7 cited

Structural Attention-Based Recurrent Variational Autoencoder for Highway Vehicle Anomaly Detection

Neeloy Chakraborty, Aamir Hasan, Shuijing Liu +4

In autonomous driving, detection of abnormal driving behaviors is essential to ensure the safety of vehicle controllers. Prior works in vehicle anomaly detection have shown that mo…

cs.RO2023

A Data-Efficient Visual-Audio Representation with Intuitive Fine-tuning for Voice-Controlled Robots

Peixin Chang, Shuijing Liu, Tianchen Ji +3

A command-following robot that serves people in everyday life must continually improve itself in deployment domains with minimal help from its end users, instead of engineers. Prev…