5 citations · 17 across the 8 of their papers we have counts for
11 papers
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…
Towards Lifelong Federated Learning in Autonomous Mobile Robots with Continuous Sim-to-Real Transfer
Xianjia Yu, Jorge Pena Queralta, Tomi Westerlund
The role of deep learning (DL) in robotics has significantly deepened over the last decade. Intelligent robotic systems today are highly connected systems that rely on DL for a var…
Federated Learning for Vision-based Obstacle Avoidance in the Internet of Robotic Things
Xianjia Yu, Jorge Peña Queralta, Tomi Westerlund
Deep learning methods have revolutionized mobile robotics, from advanced perception models for an enhanced situational awareness to novel control approaches through reinforcement l…
Analyzing General-Purpose Deep-Learning Detection and Segmentation Models with Images from a Lidar as a Camera Sensor
Yu Xianjia, Sahar Salimpour, Jorge Peña Queralta +1
Over the last decade, robotic perception algorithms have significantly benefited from the rapid advances in deep learning (DL). Indeed, a significant amount of the autonomy stack o…
Multi-Modal Lidar Dataset for Benchmarking General-Purpose Localization and Mapping Algorithms
Qingqing Li, Xianjia Yu, Jorge Peña Queralta +1
Lidar technology has evolved significantly over the last decade, with higher resolution, better accuracy, and lower cost devices available today. In addition, new scanning modaliti…