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  • 1.
    Damigos, Gerasimos
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system. Ericsson AB.
    Towards 5G-Enabled Intelligent Machines2024Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    This thesis introduces a novel framework for enabling intelligent machines and robots with the fifth-generation (5G) cellular network technology. Autonomous robots, such as Unmanned Aerial Vehicles (UAVs), Autonomous Guided Vehicles (AGVs), and more, can notably benefit from multi-agent collaboration, human supervision, or operation guidance, as well as from external computational units such as cloud edge servers, in all of which a framework to utilize reliable communication infrastructure is needed. Autonomous robots are often employed to alleviate humans by operating demanding missions such as inspection and data collection in harsh environments or time-critical operations in industrial environments - to name a few. For delivering data to other robots to maximize the effectiveness of the considered mission, for executing complex algorithms by offloading them into the edge cloud, or for including a human operator/supervisor into the loop, the 5G network and its advanced Quality of Service (QoS) features can be employed to facilitate the establishment of such a framework. This work focuses on establishing a baseline for integrating various time-critical robotics platforms and applications with a 5G network. These applications include offloading computationally intensive Model Predictive Control (MPC) algorithms for trajectory tracking of UAVs into the edge cloud, adapting data sharing in multi-robot systems based on network conditions, and enhancing network-aware surrounding autonomy components. We have identified a set of key performance indicators (KPIs) crucially affecting the performance of network-dependent robots and applications. We have proposed novel solutions and mechanisms to meet these requirements, which aim to combine traditional robotics techniques to enhance mission reliability with the exploitation of 5G features such as the QoS framework. Ultimately, our goal was to develop solutions that adhere to the essential paradigm of co-designing robotics with networks. We thoroughly evaluated all presented research using real-life platforms and 5G networks.

    Fulltekst (pdf)
    fulltext
  • 2.
    Damigos, Gerasimos
    et al.
    Ericsson Research, Luleå, Sweden.
    Lindgren, Tore
    Ericsson Research, Luleå, Sweden.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Toward 5G Edge Computing for Enabling Autonomous Aerial Vehicles2023Inngår i: IEEE Access, E-ISSN 2169-3536, Vol. 11, s. 3926-3941Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Offloading processes responsible for a robot’s control operation to external computational resources has been in the spotlight for many years. The vision of having access to a full cloud cluster for any autonomous robot has fueled many scientific fields. Such implementations rely strongly on a robust communication link between the robot and the cloud and have been tested over numerous network architectures. However, various limitations have been highlighted upon the realization of such platforms. For small-scale local deployments, technologies such as Wi-Fi, Zigbee, and blacktooth are inexpensive and easy to use but suffer from low transmit power and outdoor coverage limitations. In this study, the offloading time-critical control operations for an unmanned aerial vehicle (UAV) using cellular network technologies were evaluated and demonstrated experimentally, focusing on the 5G technology. The control process was hosted on an edge server that served as a ground control station (GCS). The server performs all the computations required for the autonomous operation of the UAV and sends the action commands back to the UAV over the 5G interface. This research focuses on analyzing the low-latency needs of a closed-loop control system that is put to the test on a real 5G network. Furthermore, practical limitations, integration challenges, the intended cellular architecture, and the corresponding Key Performance Indicators (KPIs) that correlate to the real-life behavior of the UAV are rigorously studied.

    Fulltekst (pdf)
    fulltext
  • 3.
    Damigos, Gerasimos
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Lindgren, Tore
    Ericsson Research, Laboratoriegränd 11, 977 53 Luleå, Sweden.
    Sandberg, Sara
    Ericsson Research, Laboratoriegränd 11, 977 53 Luleå, Sweden.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Performance of Sensor Data Process Offloading on 5G-Enabled UAVs2023Inngår i: Sensors, E-ISSN 1424-8220, Vol. 23, nr 2, artikkel-id 864Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Recently, unmanned aerial vehicle (UAV)-oriented applications have been growing worldwide. Thus, there is a strong interest in using UAVs for applications requiring wide-area connectivity coverage. Such applications might be power line inspection, road inspection, offshore site monitoring, wind turbine inspections, and others. The utilization of cellular networks, such as the fifth-generation (5G) technology, is often considered to meet the requirement of wide-area connectivity. This study quantifies the performance of 5G-enabled UAVs when sensor data throughput requirements are within the 5G network’s capability and when throughput requirements significantly exceed the capability of the 5G network, respectively. Our experimental results show that in the first case, the 5G network maintains bounded latency, and the application behaves as expected. In the latter case, the overloading of the 5G network results in increased latency, dropped packets, and overall degradation of the application performance. Our findings show that offloading processes requiring moderate sensor data rates work well, while transmitting all the raw data generated by the UAV’s sensors is not possible. This study highlights and experimentally demonstrates the impact of critical parameters that affect real-life 5G-enabled UAVs that utilize the edge-offloading power of a 5G cellular network.

    Fulltekst (pdf)
    fulltext
  • 4.
    Damigos, Gerasimos
    et al.
    Ericsson AB.
    Saradagi, Akshit
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Sandberg, Sara
    Ericsson AB.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Environmental Awareness Dynamic 5G QoS for Retaining Real Time Constraints in Robotic Applications2024Konferansepaper (Annet vitenskapelig)
  • 5.
    Damigos, Gerasimos
    et al.
    Ericsson Research, Luleå, Sweden.
    Seisa, Achilleas Santi
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Satpute, Sumeet Gajanan
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Lindgren, Tore
    Ericsson Research, Luleå, Sweden.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    A Resilient Framework for 5G-Edge-Connected UAVs based on Switching Edge-MPC and Onboard-PID Control2023Inngår i: 2020 IEEE 32nd International Symposium on Industrial Electronics (ISIE): Proceedings, IEEE, 2023Konferansepaper (Fagfellevurdert)
  • 6.
    Damigos, Gerasimos
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system. Ericsson Research, Ericsson, Laboratoriegränd 11, Luleå, 977 53, Norrbotten, Sweden.
    Stathoulopoulos, Nikolaos
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Koval, Anton
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Lindgren, Tore
    Ericsson Research, Ericsson, Laboratoriegränd 11, Luleå, 977 53, Norrbotten, Sweden.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Communication-Aware Control of Large Data Transmissions via Centralized Cognition and 5G Networks for Multi-Robot Map merging2024Inngår i: Journal of Intelligent and Robotic Systems, ISSN 0921-0296, E-ISSN 1573-0409, Vol. 110, nr 1, artikkel-id 22Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Multiple modern robotic applications benefit from centralized cognition and processing schemes. However, modern equipped robotic platforms can output a large amount of data, which may exceed the capabilities of modern wireless communication systems if all data is transmitted without further consideration. This research presents a multi-agent, centralized, and real-time 3D point cloud map merging scheme for ceaselessly connected robotic agents. Centralized architectures enable mission awareness to all agents at all times, making tasks such as search and rescue more effective. The centralized component is placed on an edge server, ensuring low communication latency, while all agents access the server utilizing a fifth-generation (5G) network. In addition, the proposed solution introduces a communication-aware control function that regulates the transmissions of map instances to prevent the creation of significant data congestion and communication latencies as well as address conditions where the robotic agents traverse in limited to no coverage areas. The presented framework is agnostic of the used localization and mapping procedure, while it utilizes the full power of an edge server. Finally, the efficiency of the novel established framework is being experimentally validated based on multiple scenarios.

    Fulltekst (pdf)
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