Publications

NR5G-SAM: A SLAM framework for Field Robotics Based on 5G New Radio

Published in MDPI Sensors Journal, 2023

Robot localization is a crucial task in robotic systems and is a pre-requisite for navigation. In outdoor environments, Global Navigation Satellite Systems (GNSS) have aided towards this direction, alongside laser and visual sensing. Despite their application in the field, GNSS suffers from limited availability in dense urban and rural environments. Light Detection and Ranging (LiDAR), inertial and visual methods are also prone to drift and can be susceptible to outliers due to environmental changes and illumination conditions. In this work, we propose a cellular Simultaneous Localization and Mapping (SLAM) framework based on 5G New Radio (NR) signals and inertial measurements for mobile robot localization with several gNodeB stations. The method outputs the pose of the robot along with a radio signal map based on the Received Signal Strength Indicator (RSSI) measurements for correction purposes. We then perform benchmarking against LiDAR-Inertial Odometry Smoothing and Mapping (LIO-SAM), a state-of-the-art LiDAR SLAM method, comparing performance via a simulator ground truth reference. Two experimental setups are presented and discussed using the sub-6 GHz and mmWave frequency bands for communication, while the transmission is based on down-link (DL) signals. Our results show that 5G positioning can be utilized for radio SLAM, providing increased robustness in outdoor environments and demonstrating its potential to assist in robot localization, as an additional absolute source of information when LiDAR methods fail and GNSS data is unreliable.

Recommended citation: Karfakis, Panagiotis T., Micael S. Couceiro, and David Portugal. 2023. "NR5G-SAM: A SLAM Framework for Field Robot Applications Based on 5G New Radio" Sensors 23, no. 11: 5354. https://www.mdpi.com/1424-8220/23/11/5354

Tailoring 3D Mapping Frameworks for Field Robotics

Published in IEEE ICRA IFRRIA Workshop, 2022

Mapping is an essential part for the adoption of robots in agricultural and forestry environments. Providing the robot with the ability to map its surroundings, facilitates its navigation and is necessary for implementing obstacle avoidance, without human interference. Herein we present the challenges of outdoor environments, present an overview of existing mapping frameworks and then evaluate their suitability for field applications. Two widely used mapping frameworks, OctoMap and RTAB-Map are analyzed within the Robot Operating System (ROS) ecosystem and a parametric study is carried out in order to assess their performance, under both simulated and real-world constraints. Finally this work aims to be utilized as a deployment reference guide for mobile robotic applications in outdoor environments.Mapping is an essential part for the adoption of robots in agricultural and forestry environments. Providing the robot with the ability to map its surroundings, facilitates its navigation and is necessary for implementing obstacle avoidance, without human interference. Herein we present the challenges of outdoor environments, present an overview of existing mapping frameworks and then evaluate their suitability for field applications. Two widely used mapping frameworks, OctoMap and RTAB-Map are analyzed within the Robot Operating System (ROS) ecosystem and a parametric study is carried out in order to assess their performance, under both simulated and real-world constraints. Finally this work aims to be utilized as a deployment reference guide for mobile robotic applications in outdoor environments.

Recommended citation: Karfakis, P.T.; Couceiro, M.S.; Portugal, D.; Antunes, C.H. A Comparative Study of Mobile Robot Positioning Using 5G-NR. IEEE International Conference on Robotics and Automation (ICRA) Workshop in Innovation in Forestry Robotics: Research and Industry Adoption, Philadelphia, PA, USA, 2022. https://labs.ri.cmu.edu/ifrria-icra-2022/call-for-papers/

UWB Aided Mobile Robot Localization with Neural Networks and the EKF

Published in IEEE Systems, Man and Cybernetics (SMC), 2022

This paper exploits the use of Ultra Wide Band (UWB) technology to improve the localization of robots in both indoor and outdoor environments. In order to efficiently integrate the UWB technology in existing multi-sensor architectures, such as Kalman-based, we propose two approaches to estimate the UWB position covariance values. The first approach uses statistical methods to estimate static covariance values based on data acquired a priori. The second approach adopts a neural network (NN) to capture the relationship between the positional error of the UWB data and the signal quality information, such as the Estimate Of Precision (EOP) and Received Signal Strength Indicator (RSSI). The GPS-RTK is used as ground truth and RGB-D odometry is adopted for both bench-marking and integration purposes. Position sources are fused by means of an Extended Kalman Filter (EKF). Real world experiments are conducted with a tracked mobile robot driving outdoors in a closed-loop trajectory. Results show that the NN is able to efficiently model the sensor covariances and adapt the trustworthiness of the EKF estimation, overcoming data loss by relying on the other available estimation source.

Recommended citation: P. T. Karfakis, M. S. Couceiro, D. Portugal and R. Cortesão, "UWB Aided Mobile Robot Localization with Neural Networks and the EKF," 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, 2022, pp. 93-99, doi: 10.1109/SMC53654.2022.9945357. https://ieeexplore.ieee.org/document/99453

A Comparative Study of Mobile Robot Positioning Using 5G NR

Published in IEEE ICRA IFRRIA Workshop, 2022

In this work we study the use of the 5G New Radio (NR) communication model for position tracking of a mobile robotic system. We have deployed the 5G NR in three different configurations in a simulated agricultural environment. We evaluate the impact of using different number of gNodeB (gNB) base stations and the increased topological complexity on the position estimation, using three different heuristic approaches. The setups consist of 5, 10 and 15 gNBs that communicate with the user equipment (UE) carried by the robot. The ground truth trajectory of the system is recorded and estimated by three meta-heuristics, namely Hyperbola Crossing points (HCP), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). We measure the performance according to statistical metrics such as the average prediction time, the average Euclidean Distance (ED) and their standard deviations. We provide and discuss the qualitative results derived experimentally to assess the positioning capability of 5G NR for a simulated field robotics application.

Recommended citation: Panagiotis T. Karfakis, Micael S. Couceiro, David S. Portugal, & Carlos H. Antunes. (2022). A Comparative Study of Mobile Robot Positioning Using 5G NR. ICRA 2022 Workshop in Innovation in Forestry Robotics: Research and Industry Adoption (IFRRIA), Philadelphia, Pennsylvania, United States. Zenodo. https://doi.org/10.5281/zenodo.7937189 https://doi.org/10.5281/zenodo.7937189

Mooring Chain Climbing Robot for NDT Inspection Applications

Published in International Conference Series on Climbing and Walking Robots (CLAWAR), 2018

Inspection of mooring chains is an important but dangerous and costly procedure covering inspection above and below the waterline. The paper presents initial results from the RIMCAW project which aimed at designing and building an inspection robot able to climb mooring chains and deploy NDT technologies for scanning individual links thereby detecting critical defects. The paper focuses on the design and realisation of the inchworm type novel crawler developed and tested in the TWI Middlesbrough, UK water tank

Recommended citation: Kimball, Matthew & Gmerek, Artur & Collins, Peter & Wheatley, Andrew & Shah, Kiran & Liu, Jianwei & Dissanayake, Mahesh & Caroll, Jessica & Plastropoulos, Angelos & Karfakis, Panagiotis & Sattar, Tariq & Sain, Amit & Virk, Gurvinder. (2018). MOORING CHAIN CLIMBING ROBOT FOR NDT INSPECTION APPLICATIONS. https://core.ac.uk/download/pdf/234021207.pdf

A Novel Holonomic Mobile Manipulator Robot for Construction Sites

Published in International Conference Series on Climbing and Walking Robots (CLAWAR), 2018

This article describes a novel mobile manipulator robot designed to work at height on construction sites. The robot comprises a mobile platform and a scissor lifter on which an ABB 6 dof manipulator is mounted. The mobile base is characterised by holonomic kinematics, provided by a novel designed omnidirectional wheel system that can travel directly and autonomously to desired poses. The robot was successfully tested in a construction site scenario to perform drilling tasks.

Recommended citation: Gmerek, Artur & Plastropoulos, A & Collins, Peter & Kimball, Matthew & Wheatley, A & Liu, Jianwei & Karfakis, Panagiotis & Shah, Kiran & Carroll, J & Virk, Gurvinder & Sain, Amit. (2018). A Novel Holonomic Robot Manipulator for Construction Sites. In 21st International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines Robotics Transforming the Future, Panama City, Panama, 2018,9. https://core.ac.uk/download/pdf/234021207.pdf