Literature Database Entry

sossalla2025multi-access

Peter Sossalla, "Multi-Access Edge Computing for Mobile Robots," PhD Thesis, Faculty of Electrical and Computer Engineering, Technical University of Dresden (TUD), February 2025. (Advisor: Frank H. P. Fitzek; Referees: Frank H. P. Fitzek, Falko Dressler and Aydin Sezgin)

Abstract

With the advancing deployment of 5G technology and the promise of low-latency and highly reliable wireless communication, the use of 5G connectivity for the control of mobile robots is gaining traction. These mobile robots commonly have strong latency and reliability requirements that 5G aims to fulfill. The concept of Multi-Access Edge Computing (MEC) additionally enables the offloading of computationally expensive processes from mobile systems to the edge of the network. Especially for battery-powered mobile robots, MEC can reduce the load onboard and increase the runtime. Simultaneous Localization and Mapping (SLAM) is an essential function of mobile robots to localize themselves with sensor information of the environment. With the sensor input, SLAM creates a map and simultaneously uses this map for localization. SLAM, especially Visual SLAM (vSLAM) that uses camera images as sensor input, are computationally expensive processes and are viable candidates for offloading with MEC. The estimated current position must be provided to the mobile robot with a low delay, since other functions such as navigation depend on localization. This work focuses on the wireless control of mobile robots with 5G and offloading of vSLAM with MEC. A feasibility study is presented that evaluates private 5G networks for mobile robot control use cases. This is followed by a Proof of Concept (PoC), which demonstrates offloading of a mobile robot’s functions with MEC using a 5G network. A solution for convenient and reliable control of mobile robots with Augmented Reality (AR) is presented. For this use case, adaptive camera image streaming, mapping with vSLAM and image rendering for AR glasses is offloaded with MEC. An evaluation of the influence of parameterization and system design on the processing speed of offloaded vSLAM follows. After an extensive analysis, an enhanced offloaded vSLAM system is introduced that is more resilient and less impacted by an increasing network latency. Additionally, Dynamic Visual SLAM Network Offloading (DynNet-SLAM) is proposed, an approach to orchestrate the computation of vSLAM depending on the currently measured network latency. DynNetSLAM further increases the reliability in an environment of fluctuating latency.

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Peter Sossalla

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@phdthesis{sossalla2025multi-access,
    author = {Sossalla, Peter},
    title = {{Multi-Access Edge Computing for Mobile Robots}},
    advisor = {Fitzek, Frank H. P.},
    institution = {Faculty of Electrical and Computer Engineering},
    location = {Dresden, Germany},
    month = {2},
    referee = {Fitzek, Frank H. P. and Dressler, Falko and Sezgin, Aydin},
    school = {Technical University of Dresden (TUD)},
    type = {PhD Thesis},
    year = {2025},
   }
   
   

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Last modified: 2025-04-17