Motivated by the growing importance of flexible automation in industrial environments, this article investigates the impact of wireless solutions in collaborative robotics, toward which we provide a quality of control (QoC)-based abstraction and methodology that comprehensively captures the interplay between network-induced delays, reliability, and robotic workload parameters for wireless collaborative robotics (WCR). For such a setting, we formulate a joint control-communication co-design based optimization framework to maximize the QoC across all robots, for 5G resource dimensioning. This is crucial for identifying optimal co-design parameters maximizing the QoC for limited 5G bandwidth across different topologies of robotic connectivity, prior to the deployment of these WCRs, or when selecting appropriate connectivity priority levels. We compare the performance of our proposed algorithm to different state of the art schemes in the literature. Our simulation results highlight the latency-reliability tradeoff and its implications on the control performance. We also demonstrate that our abstraction can be utilized for control-communication co-design, identifying optimal latency-reliability points in conjunction with the maximum velocity the robots operate with, while highlighting the energy gains due to co-design as well.

Rapid advancements in digitalization and artificial intelligence (AI) have catalyzed the adoption of digital twin technologies in the construction sector, enabling real-time synchronization between virtual models and physical systems. Simultaneously, on-site robotic automation has shown promise for reducing physical workloads, enhancing productivity, and contributing to sustainability goals that are key values of Industry 5.0. However, current digital twin implementations rarely incorporate multirobot construction systems, often relying on single-robot approaches or purely offline simulations. This gap hinders the realization of truly integrated construction environments that combine sensing, data analytics, wireless communications, and multirobot coordination. In response, this article proposes ConstrucTwin, a digital twin-driven multirobot construction framework designed to support complex construction tasks in real-world settings. By combining a 5G communication estimation-involved architecture and a cross-level planning strategy, ConstrucTwin streamlines interactions between physical robots and their digital counterparts. Essential tasks such as motion and task-level planning, as well as remote human-in-the-loop (HIL) oversight, are orchestrated within a single unified architecture. Through case studies involving rebar cage and brick wall construction, we demonstrate how an integrated approach to vision-based servoing and multirobot coordination enhances execution speed, precision, and scalability. The results underscore the system’s potential to advance human-centric, resilient, and sustainable construction, thereby aligning with the broader vision of Industry 5.0.

The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of Service (QoS) features. Despite the prevalence of 5G QoS discussions in the related literature, there is a notable absence of real-life implementations and studies concerning their application in time-critical robotics scenarios. This article considers the operation of time-critical applications for 5G-enabled unmanned aerial vehicles (UAVs) and how their operation can be improved by the possibility to dynamically switch between QoS data flows with different priorities. As such, we introduce a robotics oriented analysis on the impact of the 5G QoS functionality on the performance of 5G-enabled UAVs. Furthermore, we introduce a novel framework for the dynamic selection of distinct 5G QoS data flows that is autonomously managed by the 5G-enabled UAV. This problem is addressed in a novel feedback loop fashion utilizing a probabilistic finite state machine (PFSM). Finally, the efficacy of the proposed scheme is experimentally validated with a 5G-enabled UAV in a real-world 5G stand-alone (SA) network. https://www.youtube.com/watch?v=lWtMOlVMEFI&t=1s

The paper builds up on the idea of separating, in the time dimension, between conventional uncoordinated MIMO and IA transmission. The former usually utilizes all available dimensions (antennas) to send useful information, while the latter mitigates inter-cell interference. Due to the multitude of users in cellular networks, the transmission schemes are suitable for different groups of users. Therefore, in order to take advantage of both schemes, the users are classified into two groups: one with those users that supposedly benefit from cooperation and the other with those that should not cooperate. The proposed method for grouping the users has the advantage of being based on a simple decision metric, which avoids having to calculate precoders for all different possible combinations. Since each group must apply the proper transmission scheme, a fraction of the temporal resources is dedicated to each type of transmission. An automatic reservation of the temporal resources and an adaptive adjustment of the grouping threshold for each user, which avoids having to empirically determine a single threshold, are also proposed. These proposed mechanisms are shown to provide performance gains of up to 30% over the conventional transmissions.

This paper analyzes construction algorithms for low-density parity-check (LDPC) codes with respect to their unequal error protection (UEP) capabilities. We show that the choice of code construction algorithm highly affects the performance and UEP properties of LDPC codes with identical degree distributions. Our results provide an explanation to disagreements in earlier research.

This paper presents a strategy for the design of bandwidth-efficient LDPC codes with unequal error protection. Bandwidth efficiency is obtained by appropriately designing the codes for higher order constellations, assuming an AWGN channel. The irregularities of the LDPC code are designed, using the Gaussian approximation of the density evolution, to enhance the unequal error protection property of the code as well as account for the different bit error probabilities given by the higher order constellation. The proposed code design algorithm is flexible in terms of the number and proportions of protection classes. It also allows arbitrary modulation schemes. Our method combines the design of unequal error protection LDPC codes for the binary input AWGN channel with the code design for higher order constellations by dividing the variable node degree distribution into sub-degree distributions for each protection class and each level of protection from the modulation. The results show that appropriate code design for higher order constellations reduces the overall bit-error rate significantly. Furthermore, the unequal error protection capability of the code is increased, especially for high SNR.

We present an optimization method for unequal error protection (UEP)-LDPC codes with higher order constellations. By modifying the density evolution algorithm under the Gaussian approximation, we propose a flexible code design algorithm for a variable number of protection classes and arbitrary modulation schemes with Gray mapping. Our results show that appropriate code design for higher order constellations reduces the overall bit-error rate. Furthermore, the influence on the UEP capability of the code, that is, the difference in bit-error rate between the protection classes, is investigated.