74 citations · 187 across the 30 of their papers we have counts for
33 papers
Generalizable 6D Pose Estimation of Textureless Objects with Planar-based Gaussian Splatting
Jie Lu, Hengtan Zhang, Li Gong +7
Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the lack of appearance features. While recent generalizable approaches al…
Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments
Ali Salmasi, Xianjia Yu, Tomi Westerlund
Foundation-model-based vision-language navigation (VLN) has advanced autonomous robot navigation by enabling robots to interpret natural-language instructions, identify semantic go…
SAFEVPR: Patch-Based Conformal Verification for Safe Cross-Condition Sequence Visual Place Recognition
Ha Sier, Jiaqiang Zhang, Zhuo Zou +2
Sequence-based visual place recognition (VPR) for SLAM and robot relocalization must decide whether the retrieved top-1 candidate is safe to accept. Conformal prediction is a natur…
Seamless Outdoor-Indoor Pedestrian Positioning System with GNSS/UWB/IMU Fusion: A Comparison of EKF, FGO, and PF
Jiaqiang Zhang, Xianjia Yu, Sier Ha +5
Accurate and continuous pedestrian positioning across outdoor-indoor environments remains challenging because GNSS, UWB, and inertial PDR are complementary yet individually fragile…
A Sensor-Aware Phenomenological Framework for Lidar Degradation Simulation and SLAM Robustness Evaluation
Doumegna Mawuto Koudjo Felix, Xianjia Yu, Zhuo Zou +1
Lidar-based SLAM systems are highly sensitive to adverse conditions such as occlusion, noise, and field-of-view (FoV) degradation, yet existing robustness evaluation methods either…
Degradation-Aware Cooperative Multi-Modal GNSS-Denied Localization Leveraging LiDAR-Based Robot Detections
Václav Pritzl, Xianjia Yu, Tomi Westerlund +2
Accurate long-term localization using onboard sensors is crucial for robots operating in Global Navigation Satellite System (GNSS)-denied environments. While complementary sensors…
Lidar Variability: A Novel Dataset and Comparative Study of Solid-State and Spinning Lidars
Doumegna Mawuto Koudjo Felix, Xianjia Yu, Jiaqiang Zhang +3
Lidar technology has been widely employed across various applications, such as robot localization in GNSS-denied environments and 3D reconstruction. Recent advancements have introd…
Blockchain-Enabled Privacy-Preserving Second-Order Federated Edge Learning in Personalized Healthcare
Anum Nawaz, Muhammad Irfan, Xianjia Yu +4
Federated learning (FL) is increasingly recognised for addressing security and privacy concerns in traditional cloud-centric machine learning (ML), particularly within personalised…
Blockchain Powered Edge Intelligence for U-Healthcare in Privacy Critical and Time Sensitive Environment
Anum Nawaz, Hafiz Humza Mahmood Ramzan, Xianjia Yu +2
Edge Intelligence (EI) serves as a critical enabler for privacy-preserving systems by providing AI-empowered computation and distributed caching services at the edge, thereby minim…
Enhancing Lidar Point Cloud Sampling via Colorization and Super-Resolution of Lidar Imagery
Sier Ha, Honghao Du, Xianjia Yu +1
Recent advancements in lidar technology have led to improved point cloud resolution as well as the generation of 360 degrees, low-resolution images by encoding depth, reflectivity,…
Event-based Sensor Fusion and Application on Odometry: A Survey
Jiaqiang Zhang, Xianjia Yu, Ha Sier +2
Event cameras, inspired by biological vision, are asynchronous sensors that detect changes in brightness, offering notable advantages in environments characterized by high-speed mo…
Dual-Criterion Model Aggregation in Federated Learning: Balancing Data Quantity and Quality
Haizhou Zhang, Xianjia Yu, Tomi Westerlund
Federated learning (FL) has become one of the key methods for privacy-preserving collaborative learning, as it enables the transfer of models without requiring local data exchange.…
Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery
Sier Ha, Honghao Du, Xianjia Yu +2
Modern lidar systems can produce not only dense point clouds but also 360 degrees low-resolution images. This advancement facilitates the application of deep learning (DL) techniqu…
Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset
Iacopo Catalano, Xianjia Yu, Jorge Pena Queralta
With the increasing prevalence of drones in various industries, the navigation and tracking of unmanned aerial vehicles (UAVs) in challenging environments, particularly GNSS-denied…
LiDAR-Generated Images Derived Keypoints Assisted Point Cloud Registration Scheme in Odometry Estimation
Haizhou Zhang, Xianjia Yu, Sier Ha +1
Keypoint detection and description play a pivotal role in various robotics and autonomous applications including visual odometry (VO), visual navigation, and Simultaneous localizat…
Comparison of Middlewares in Edge-to-Edge and Edge-to-Cloud Communication for Distributed ROS2 Systems
Jiaqiang Zhang, Xianjia Yu, Sier Ha +2
The increased data transmission and number of devices involved in communications among distributed systems make it challenging yet significantly necessary to have an efficient and…
Benchmarking UWB-Based Infrastructure-Free Positioning and Multi-Robot Relative Localization: Dataset and Characterization
Paola Torrico Morón, Sahar Salimpour, Lei Fu +3
Ultra-wideband (UWB) positioning has emerged as a low-cost and dependable localization solution for multiple use cases, from mobile robots to asset tracking within the Industrial I…
UAV Tracking with Solid-State Lidars:Dynamic Multi-Frequency Scan Integration
Iacopo Catalano, Ha Sier, Xianjia Yu +2
With the increasing use of drones across various industries, the navigation and tracking of these unmanned aerial vehicles (UAVs) in challenging environments (such as GNSS-denied e…
Fusing Odometry, UWB Ranging, and Spatial Detections for Relative Multi-Robot Localization
Xianjia Yu, Iacopo Catalano, Paola Torrico Morón +3
This letter presents a cooperative relative multi-robot localization design and experimental study. We propose a flexible Monte Carlo approach leveraging a particle filter to estim…
Robust Multi-Modal Multi-LiDAR-Inertial Odometry and Mapping for Indoor Environments
Li Qingqing, Yu Xianjia, Jorge Peña Queralta +1
Integrating multiple LiDAR sensors can significantly enhance a robot's perception of the environment, enabling it to capture adequate measurements for simultaneous localization and…
Exploiting Redundancy for UWB Anomaly Detection in Infrastructure-Free Multi-Robot Relative Localization
Sahar Salimpour, Paola Torrico Morón, Xianjia Yu +2
Ultra-wideband (UWB) localization methods have emerged as a cost-effective and accurate solution for GNSS-denied environments. There is a significant amount of previous research in…
UAV Tracking with Lidar as a Camera Sensors in GNSS-Denied Environments
Ha Sier, Xianjia Yu, Iacopo Catalano +3
LiDAR has become one of the primary sensors in robotics and autonomous system for high-accuracy situational awareness. In recent years, multi-modal LiDAR systems emerged, and among…
Distributed Robotic Systems in the Edge-Cloud Continuum with ROS 2: a Review on Novel Architectures and Technology Readiness
Jiaqiang Zhang, Farhad Keramat, Xianjia Yu +3
Robotic systems are more connected, networked, and distributed than ever. New architectures that comply with the \textit{de facto} robotics middleware standard, ROS\,2, have recent…
A Benchmark for Multi-Modal Lidar SLAM with Ground Truth in GNSS-Denied Environments
Ha Sier, Li Qingqing, Yu Xianjia +3
Lidar-based simultaneous localization and mapping (SLAM) approaches have obtained considerable success in autonomous robotic systems. This is in part owing to the high-accuracy of…