26 citations · 30 across the 5 of their papers we have counts for
7 papers
SUPER ODOMETRY 2.0: Resilient Odometry via Hierarchical Adaptation
Shibo Zhao, Sifan Zhou, Yuchen Zhang +4
Resilient and robust odometry is crucial for autonomous systems operating in complex and dynamic environments. Existing odometry systems often struggle with severe sensory degradat…
SuperMap: A Spatio-Temporal SLAM System for Visual-Language Navigation
Shibo Zhao, Guofei Chen, Honghao Zhu +7
Robotic navigation in human environments requires a spatio-temporal semantic representation that can rec- oncile open-vocabulary perception with long-term environmental changes. Wh…
Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video
Xiaohao Xu, Tianyi Zhang, Shibo Zhao +8
We aim to redefine robust ego-motion estimation and photorealistic 3D reconstruction by addressing a critical limitation: the reliance on noise-free data in existing models. While…
AirIO: Learning Inertial Odometry with Enhanced IMU Feature Observability
Yuheng Qiu, Can Xu, Yutian Chen +3
Inertial odometry (IO) using only Inertial Measurement Units (IMUs) offers a lightweight and cost-effective solution for Unmanned Aerial Vehicle (UAV) applications, yet existing le…
MAC-Ego3D: Multi-Agent Gaussian Consensus for Real-Time Collaborative Ego-Motion and Photorealistic 3D Reconstruction
Xiaohao Xu, Feng Xue, Shibo Zhao +3
Real-time multi-agent collaboration for ego-motion estimation and high-fidelity 3D reconstruction is vital for scalable spatial intelligence. However, traditional methods produce s…
SuperLoc: The Key to Robust LiDAR-Inertial Localization Lies in Predicting Alignment Risks
Shibo Zhao, Honghao Zhu, Yuanjun Gao +4
Map-based LiDAR localization, while widely used in autonomous systems, faces significant challenges in degraded environments due to lacking distinct geometric features. This paper…
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…