36 citations · 120 across the 10 of their papers we have counts for
11 papers · 1 filter
RoMo-GS: Efficient Online 3D Gaussian Splatting for Robot Mapping via Exposure-Integrated Motion Blur
Sangwoo Jung, Di Deng, Jiahui Fu +3
Online 3D Gaussian Splatting (3DGS) is emerging as a practical way to build a representation for robotics applications. However, deploying it on real-world platforms exposes multip…
Test-Time Spatial Reasoning for Robot Manipulation Using Generative Real-to-Sim
Ivan Kapelyukh, Yafei Hu, Ran Gong +6
Spatial reasoning is fundamental to general robot intelligence, as it enables robots to complete long-horizon tasks involving multi-object interaction. We introduce Simify, a train…
Efficient Sim-to-Real Transfer of World-Action Models from Synthetic Priors
Zixing Wang, Kausik Sivakumar, Jinghuan Shang +5
Bridging the sim-to-real gap is a core challenge in deploying learned manipulation policies. Sim-to-real learning is attractive because it can replace expensive real robot demonstr…
EMPM: Embodied MPM for Modeling and Simulation of Deformable Objects
Yunuo Chen, Yafei Hu, Lingfeng Sun +3
Modeling deformable objects - especially continuum materials - in a way that is physically plausible, generalizable, and data-efficient remains challenging across 3D vision, graphi…
GaRLILEO: Gravity-aligned Radar-Leg-Inertial Enhanced Odometry
Chiyun Noh, Sangwoo Jung, Hanjun Kim +3
Deployment of legged robots for navigating challenging terrains (e.g., stairs, slopes, and unstructured environments) has gained increasing preference over wheel-based platforms. I…
NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos
Hongyu Li, Lingfeng Sun, Yafei Hu +4
Enabling robots to execute novel manipulation tasks zero-shot is a central goal in robotics. Most existing methods assume in-distribution tasks or rely on fine-tuning with embodime…
Learning Generalizable Feature Fields for Mobile Manipulation
Ri-Zhao Qiu, Yafei Hu, Yuchen Song +8
An open problem in mobile manipulation is how to represent objects and scenes in a unified manner so that robots can use both for navigation and manipulation. The latter requires c…
Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Yafei Hu, Quanting Xie, Vidhi Jain +20
Building general-purpose robots that operate seamlessly in any environment, with any object, and utilizing various skills to complete diverse tasks has been a long-standing goal in…
Off-Policy Evaluation with Online Adaptation for Robot Exploration in Challenging Environments
Yafei Hu, Junyi Geng, Chen Wang +2
Autonomous exploration has many important applications. However, classic information gain-based or frontier-based exploration only relies on the robot current state to determine th…
Unsupervised Online Learning for Robotic Interestingness with Visual Memory
Chen Wang, Yuheng Qiu, Wenshan Wang +3
Autonomous robots frequently need to detect "interesting" scenes to decide on further exploration, or to decide which data to share for cooperation. These scenarios often require f…
TartanAir: A Dataset to Push the Limits of Visual SLAM
Wenshan Wang, Delong Zhu, Xiangwei Wang +6
We present a challenging dataset, the TartanAir, for robot navigation tasks and more. The data is collected in photo-realistic simulation environments with the presence of moving o…