140 citations · 159 across the 15 of their papers we have counts for
17 papers
LynxScenes: A Large-Scale Real-World Benchmark for Outdoor Wheel-Legged Robot Perception, Navigation, Imagination and Reconstruction
Jun Tian, Hao Wu, Ruo Chen +5
Wheel-legged robots operating in outdoor spaces shared with humans require accurate perception, socially compliant navigation, future-scene reasoning, and scene reconstruction. How…
C2Flight: A Closed-Loop Co-Simulation Framework for Early-Stage Evaluation of Heterogeneous UAV Computing Systems
Xizhu Chen, Shuyuan Zhang, Yixuan Li +4
Early-stage design of heterogeneous UAV computing systems requires evaluating how algorithm, hardware, communication, and system topology affect closed-loop flight before the compl…
RoboDrop: Curating VLA Post-Training Data via Local Gradient Compatibility
Runze Xu, Yuanfan Xu, Cuijie Xu +4
Vision--language--action (VLA) models acquire broad generalization through large-scale pretraining, yet adapting them to a new task and robot embodiment still requires post-trainin…
Knowing When to Stop: Adaptive Action Chunking via Internal Cross-Attention Dynamics in VLAs
Runze Xu, Xiaolong Shan, Shuang Dai +2
Action chunking is a standard execution strategy in modern Vision-Language-Action (VLA) frameworks, but fixed execution horizons impose a trade-off between efficiency and accuracy.…
The Curse of Precision: A Data Scaling Law for High-Precision Robotic Manipulation
Cuijie Xu, Yuanfan Xu, Min Xue +5
While scaling laws for imitation learning have primarily focused on generalization in open-world settings, the relationship between data and precision in closed-world tasks like ro…
Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos
Runze Xu, Yiluo Zhang, Jian Wang +2
Training generalist Vision-Language-Action(VLA) models typically requires massive, diverse robotic datasets with high-fidelity action annotations. While egocentric human manipulati…
HCLM: A Hierarchical Framework for Cooperative Loco-Manipulation with Dual Quadrupeds
Qixuan Li, Chen Le, Jincheng Yu +1
We introduce HCLM, a hierarchical framework for general-purpose cooperative loco-manipulation with dual quadrupedal systems. Coordinating multi-robot collaborative manipulation acr…
ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation
Yu Sun, Meng Cao, Yang Ping +24
Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their empirical progress remains constra…
COMPASS: Confined-space Manipulation Planning with Active Sensing Strategy
Qixuan Li, Chen Le, Dongyue Huang +2
Manipulation in confined and cluttered environments remains a significant challenge due to partial observability and complex configuration spaces. Effective manipulation in such en…
MR-COGraphs: Communication-efficient Multi-Robot Open-vocabulary Mapping System via 3D Scene Graphs
Qiuyi Gu, Zhaocheng Ye, Jincheng Yu +7
Collaborative perception in unknown environments is crucial for multi-robot systems. With the emergence of foundation models, robots can now not only perceive geometric information…
Localization matters too: How localization error affects UAV flight
Suquan Zhang, Yuanfan Xu, Shu'ang Yu +3
The maximum safe flight speed of a Unmanned Aerial Vehicle (UAV) is an important indicator for measuring its efficiency in completing various tasks. This indicator is influenced by…
Point Cloud Change Detection With Stereo V-SLAM:Dataset, Metrics and Baseline
Zihan Lin, Jincheng Yu, Lipu Zhou +3
Localization and navigation are basic robotic tasks requiring an accurate and up-to-date map to finish these tasks, with crowdsourced data to detect map changes posing an appealing…
Explore-Bench: Data Sets, Metrics and Evaluations for Frontier-based and Deep-reinforcement-learning-based Autonomous Exploration
Yuanfan Xu, Jincheng Yu, Jiahao Tang +5
Autonomous exploration and mapping of unknown terrains employing single or multiple robots is an essential task in mobile robotics and has therefore been widely investigated. Never…
Multi-UAV Coverage Planning with Limited Endurance in Disaster Environment
Hongyu Song, Jincheng Yu, Jiantao Qiu +5
For scenes such as floods and earthquakes, the disaster area is large, and rescue time is tight. Multi-UAV exploration is more efficient than a single UAV. Existing UAV exploration…
Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes
Feng Gao, Jincheng Yu, Hao Shen +2
Learning depth and ego-motion from unlabeled videos via self-supervision from epipolar projection can improve the robustness and accuracy of the 3D perception and localization of v…
Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks
Wenshuo Li, Jincheng Yu, Xuefei Ning +4
Recently, Deep Learning (DL), especially Convolutional Neural Network (CNN), develops rapidly and is applied to many tasks, such as image classification, face recognition, image se…
A Survey of FPGA-Based Neural Network Accelerator
Kaiyuan Guo, Shulin Zeng, Jincheng Yu +2
Recent researches on neural network have shown significant advantage in machine learning over traditional algorithms based on handcrafted features and models. Neural network is now…