14 papers
Physical SLAM: Physics-aware Simultaneous Localisation and Mapping
Guangming Wang, Zhishuo Liu, Haibing Wu +4
To reconstruct a predictive 4D representation of the physical world from monocular video captured by a moving camera, we jointly reconstruct dynamic Gaussian radiance fields and in…
SwingRL: Adaptive Observation Reinforcement Learning with World-Model Prediction for Cable-Suspended Hoisting Control
Guangming Wang, Xiaoyu Zhang, Yucheng Xin +8
Cable-suspended hoisting is widely used to move heavy or bulky payloads that cannot be handled conveniently by rigid pick-and-place systems, for example in crane-assisted construct…
R4Tun: LLM-guided adaptive segmental tunnel lining segmentation in point clouds
Xinghui Tao, Zehao Ye, Guangming Wang +2
Automated inspection of segmental tunnel linings requires adaptive segmentation from 3D point clouds, yet expert-tuned pipelines often degrade when tunnel conditions vary. This pap…
A Brain-inspired Hierarchical Framework for Zero-Shot Robot Task Reasoning and Execution
Guangming Wang, Pengfei Ye, Qizhen Ying +7
Robots that follow open-ended language instructions need to connect semantic intent to visual scene understanding, geometric feasibility, object states, and physical interaction co…
SeqLoc: Beyond the Single Frame for Cross-View Geo-Localization in Feature-Sparse Scenes
Junwei Zheng, Yun Huang, Ruize Dai +8
Cross-View Geo-Localization (CVGL) with OpenStreetMap (OSM) performs well in structure-rich urban environments but collapses in feature-sparse scenes such as rural roads. To study…
BendTwin: Robust Dense-to-Sparse Physical Reconstruction with Bending-Aware Differentiable Spring-Mass Models
Yixiong Jing, Qi Wang, Lin Chen +6
Reconstructing objects with mechanical properties from video observations enables physically consistent dynamic prediction, benefiting robotics planning and interaction. Existing s…
You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact
Pengfei Ye, Yuxiang Ma, Haonan Chen +5
Accurate 6-DoF object pose estimation is fundamental to robotic manipulation, yet vision-based methods often fail under occlusion, poor lighting, and reflective or transparent surf…
SemCityLoc: Aerial 6DoF Localization Using Semantic 3D City Models
Jingfeng Mao, Xuyang Chen, Qilin Zhang +6
Aerial 6DoF localization typically relies on precise GNSS signals or radiometrically rich 3D reconstructions, limiting scalability and on-board deployment. We propose SemCityLoc, a…
NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics
Qizhen Ying, Guangming Wang, Yangchen Pan +3
Physics-grounded video generation requires controllable 3D object dynamics that remain physically consistent under contact, deformation, and external forcing. Existing trajectory-b…
RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation
Sixu Lin, Junliang Chen, Huaiyuan Xu +8
Planning and acting in 3D environments is a fundamental capability for robotic manipulation in the real world. Although prior work has explored predictive flow planners to guide 3D…
PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN
Yixiong Jing, Xingyuan Chen, Guangming Wang +3
Physics-based digital twins aim to predict the dynamics of real-world objects under interaction, enabling real-to-sim-to-real applications in robotics. Current approaches reconstru…
ActionReasoning: Robot Action Reasoning in 3D Space with LLM for Robotic Brick Stacking
Guangming Wang, Qizhen Ying, Yixiong Jing +2
Classical robotic systems typically rely on custom planners designed for constrained environments. While effective in restricted settings, these systems lack generalization capabil…
Continually Evolving Skill Knowledge in Vision Language Action Model
Yuxuan Wu, Guangming Wang, Zhiheng Yang +4
Vision-language-action (VLA) models show promising knowledge accumulation ability through pretraining, yet continual learning remains challenging. Existing continual imitation lear…
InfraDiffusion: zero-shot depth map restoration with diffusion models and prompted segmentation from sparse infrastructure point clouds
Yixiong Jing, Cheng Zhang, Haibing Wu +3
Point clouds are widely used for infrastructure monitoring by providing geometric information, where segmentation is required for downstream tasks such as defect detection. Existin…