Ing. Adam Jáneš

The rapid evolution of 5G and the emergence of 6G mobile networks unlock transformative possibilities for collaborative robotics, with a particular emphasis on teleoperation systems that demand high-quality, low-latency communication. However, progress in teleoperation and communication remains fragmented, as researchers in these fields often lack interdisciplinary expertise and access to essential experimental infrastructure, including advanced robotic platforms and 5G/6G testbeds. The interdisciplinary expertise and infrastructure gap hinder the cross-disciplinary collaboration required to advance collaborative robotics using next-generation networks. In this paper, we introduce the concept of a Remote Experience Center to address this gap, demonstrating its implementation through a teleoperation framework that integrates a software-defined mobile network deployed in Prague with a robotic platform situated in Munich. We perform two classical teleoperation tasks, pick-and-place and peg-in-hole, transmitting robot control signals, as well as visual and force feedback, over the software-defined mobile network in Prague to a robotic platform and human operator located in Munich. To enhance research safety and ensure broader accessibility to our framework, we also offer a digital twin of the robotic platform. Via real-world experiments, we evaluate the impact of latency and packet loss on user satisfaction with our framework.

We focus on computation offloading from moving devices, such as mobile robots or autonomous vehicles to MultiAccess Edge Computing (MEC) servers via mobile network. To this end, we develop and implement a prototype of small autonomous vehicle with capability to offload processing of sensor data to MEC server via mobile network. Then, we investigate an impact of communication channel on delay and energy consumed by the autonomous vehicle for two practical applications, namely road sign recognition and path planning, in the real-world environment with a real physical equipment. Via experiments, we demonstrate benefits of the computation offloading on both energy and delay. The experiments highlight the potential of MEC for the autonomous systems allowing to reduce cost and increase scalability of such autonomous systems. Furthermore, based on the real-world experiments, we derive detailed models of energy consumption and delay for both practical applications.

The rapid development of mobile networks opens new possibilities for collaborative robotics, particularly teleoper- ation, which requires highly reliable communication with low- latency. Nevertheless, researchers often face challenges due to limited cross-disciplinary expertise and restricted access to exper- imental infrastructure, such as advanced robotic platforms and 5G/6G testbeds. To address the fragmentation in teleoperation research, we present a modular experimental framework with graphical user interface (GUI), labeled as the Remote Experience Center (REC), which enables real-time robotic control over software-defined mobile networks. The REC integrates a mobile network testbed deployed in Prague with a robotic platform located in Munich. We demonstrate capabilities of the REC through a pick-and-place task involving human control with visual and force feedback. To improve safety and accessibility, the REC includes not only real hardware, but also digital twin of both the robotic system and the mobile network. Through real-world experiments, we investigate the impact of key mobile network parameters and characteristics, such as modulation and coding scheme (MCS), communication delay, and jitter, on user experience and system responsiveness. The experimental results reveal that increasing communication delay and jitter, as well as decreasing MCS, negatively affect the conditions for performing teleoperation tasks over a mobile network.