1 citations · 1 across the 12 of their papers we have counts for
15 papers
Teach and Grow: An Agent-Centered Architecture for General Robot Learning
Chang Nie, Zhe Liu, Hesheng Wang
Vision-language-action (VLA) and world-action models typically absorb unfamiliar manipulation tasks through additional robot data collection and policy optimization. This recurring…
Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series
Ruichao Guo, Xingyao Han, Luo Wenshui +3
Point forecasting for graph-structured multivariate time series is a fundamental problem, but rigorous uncertainty quantification for such predictions is still underexplored. Confo…
POMDP-based Object Search with Growing State Space and Hybrid Action Domain
Yongbo Chen, Hesheng Wang, Shoudong Huang +1
Efficiently locating target objects in complex indoor environments with diverse furniture, such as shelves, tables, and beds, is a significant challenge for mobile robots. This dif…
Keep It CALM: Toward Calibration-Free Kilometer-Level SLAM with Visual Geometry Foundation Models via an Assistant Eye
Tianjun Zhang, Fengyi Zhang, Tianchen Deng +2
Visual Geometry Foundation Models (VGFMs) demonstrate remarkable zero-shot capabilities in local reconstruction. However, deploying them for kilometer-level Simultaneous Localizati…
RESBev: Making BEV Perception More Robust
Lifeng Zhuo, Kefan Jin, Zhe Liu +1
Bird's-eye-view (BEV) perception has emerged as a cornerstone of autonomous driving systems, providing a structured, ego-centric representation critical for downstream planning and…
MID: A Self-supervised Multimodal Iterative Denoising Framework
Chang Nie, Tianchen Deng, Zhe Liu +1
Data denoising is a persistent challenge across scientific and engineering domains. Real-world data is frequently corrupted by complex, non-linear noise, rendering traditional rule…
DIAL-GS: Dynamic Instance Aware Reconstruction for Label-free Street Scenes with 4D Gaussian Splatting
Chenpeng Su, Wenhua Wu, Chensheng Peng +3
Urban scene reconstruction is critical for autonomous driving, enabling structured 3D representations for data synthesis and closed-loop testing. Supervised approaches rely on cost…
Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation
Yiyuan Pan, Yunzhe Xu, Zhe Liu +1
Visual navigation is a fundamental problem in embodied AI, yet practical deployments demand long-horizon planning capabilities to address multi-objective tasks. A major bottleneck…
MRASfM: Multi-Camera Reconstruction and Aggregation through Structure-from-Motion in Driving Scenes
Lingfeng Xuan, Chang Nie, Yiqing Xu +3
Structure from Motion (SfM) estimates camera poses and reconstructs point clouds, forming a foundation for various tasks. However, applying SfM to driving scenes captured by multi-…
Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
Yiyuan Pan, Zhe Liu, Hesheng Wang
Autonomous exploration in complex multi-agent reinforcement learning (MARL) with sparse rewards critically depends on providing agents with effective intrinsic motivation. While ar…
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking
Chang Nie, Yiqing Xu, Guangming Wang +3
Moving object segmentation plays a vital role in understanding dynamic visual environments. While existing methods rely on multi-frame image sequences to identify moving objects, s…
Planning from Imagination: Episodic Simulation and Episodic Memory for Vision-and-Language Navigation
Yiyuan Pan, Yunzhe Xu, Zhe Liu +1
Humans navigate unfamiliar environments using episodic simulation and episodic memory, which facilitate a deeper understanding of the complex relationships between environments and…
PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments
Haoang Li, Xiangqi Meng, Xingxing Zuo +3
Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many method…
Enhancing Exploratory Capability of Visual Navigation Using Uncertainty of Implicit Scene Representation
Yichen Wang, Qiming Liu, Zhe Liu +1
In the context of visual navigation in unknown scenes, both "exploration" and "exploitation" are equally crucial. Robots must first establish environmental cognition through explor…
FLAME: Learning to Navigate with Multimodal LLM in Urban Environments
Yunzhe Xu, Yiyuan Pan, Zhe Liu +1
Large Language Models (LLMs) have demonstrated potential in Vision-and-Language Navigation (VLN) tasks, yet current applications face challenges. While LLMs excel in general conver…