activity
20202026
most citedMulti Sensor Fusion for Navigation and Mapping in Autonomous Vehicles: Accurate Localization in Urban Environments

109 citations · 261 across the 15 of their papers we have counts for

collaborators

15 papers

cs.RO2026★ 2 cited

SAHA: Supervised Autonomous HArvester for selective forest thinning

Fang Nan, Meher Malladi, Qingqing Li +7

Forestry plays a vital role in our society, creating significant ecological, economic, and recreational value. Efficient forest management involves labor-intensive and complex oper…

cs.RO2023★ 2 cited

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…

cs.RO2022★ 1 cited

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…

cs.RO2022★ 5 cited

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…

cs.RO2021★ 3 cited

Adaptive Lidar Scan Frame Integration: Tracking Known MAVs in 3D Point Clouds

Li Qingqing, Yu Xianjia, Jorge Peña Queralta +1

Micro-aerial vehicles (MAVs) are becoming ubiquitous across multiple industries and application domains. Lightweight MAVs with only an onboard flight controller and a minimal senso…

cs.RO2021★ 2 cited

Cooperative UWB-Based Localization for Outdoors Positioning and Navigation of UAVs aided by Ground Robots

Yu Xianjia, Li Qingqing, Jorge Pena Queralta +2

Unmanned aerial vehicles (UAVs) are becoming largely ubiquitous with an increasing demand for aerial data. Accurate navigation and localization, required for precise data collectio…

cs.RO2021★ 45 cited

Applications of UWB Networks and Positioning to Autonomous Robots and Industrial Systems

Xianjia Yu, Qingqing Li, Jorge Peña Queralta +2

Ultra-wideband (UWB) technology is a mature technology that contested other wireless technologies in the advent of the IoT but did not achieve the same levels of widespread adoptio…

cs.RO2021★ 109 cited

Multi Sensor Fusion for Navigation and Mapping in Autonomous Vehicles: Accurate Localization in Urban Environments

Li Qingqing, Jorge Peña Queralta, Tuan Nguyen Gia +2

The combination of data from multiple sensors, also known as sensor fusion or data fusion, is a key aspect in the design of autonomous robots. In particular, algorithms able to acc…

cs.RO2021★ 2 cited

Towards Large-Scale Scalable MAV Swarms with ROS2 and UWB-based Situated Communication

Jorge Peña Queralta, Yu Xianjia, Li Qingqing +1

The design and development of swarms of micro-aerial vehicles (MAVs) has recently gained significant traction. Collaborative aerial swarms have potential applications in areas as d…

cs.RO2020★ 15 cited

VIO-UWB-Based Collaborative Localization and Dense Scene Reconstruction within Heterogeneous Multi-Robot Systems

Jorge Peña Queralta, Li Qingqing, Fabrizio Schiano +1

Effective collaboration in multi-robot systems requires accurate and robust estimation of relative localization: from cooperative manipulation to collaborative sensing, and includi…

cs.RO2020★ 10 cited

Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots

Jorge Peña Queralta, Li Qingqing, Eduardo Castelló Ferrer +1

As autonomous robots are becoming more widespread, more attention is being paid to the security of robotic operation. Autonomous robots can be seen as cyber-physical systems: they…

cs.LG2020★ 2 cited

Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning

Wenshuai Zhao, Jorge Peña Queralta, Li Qingqing +1

Current research directions in deep reinforcement learning include bridging the simulation-reality gap, improving sample efficiency of experiences in distributed multi-agent reinfo…

cs.RO2020★ 1 cited

Ubiquitous Distributed Deep Reinforcement Learning at the Edge: Analyzing Byzantine Agents in Discrete Action Spaces

Wenshuai Zhao, Jorge Peña Queralta, Li Qingqing +1

The integration of edge computing in next-generation mobile networks is bringing low-latency and high-bandwidth ubiquitous connectivity to a myriad of cyber-physical systems. This…

cs.DC2020

Enhancing Autonomy with Blockchain and Multi-Access Edge Computing in Distributed Robotic Systems

Jorge Peña Queralta, Li Qingqing, Zhuo Zou +1

This conceptual paper discusses how different aspects involving the autonomous operation of robots and vehicles will change when they have access to next-generation mobile networks…

cs.RO2020★ 62 cited

Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation

Qingqing Li, Paavo Nevalainen, Jorge Peña Queralta +2

Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest.…