Abstract
Rising industrial complexity demands efficient mobile robots to drive automation and productivity. Effective navigation relies on perception, localization, mapping, path planning, and motion control, with path planning being key. The Time Enhanced A* (TEA*) algorithm extends A* by adding time as a dimension to resolve temporal conflicts in multi-robot coordination. However, inconsistencies in edge lengths within the graph can hinder optimal path calculation. To address this, a Graph Decomposition submodule was developed to standardize edge lengths and temporal costs. Integrated into a ROS-based fleet coordination system, this approach significantly reduces execution time and improves coordination capacity.

Abstract
Energy community developers are relevant actors for the deployment of energy communities as they can overcome initial investment costs and better navigate complex licensing processes. Their strategy depends on the chosen business model, typically aimed at maximizing their profit while providing tangible benefits to the potential members of the energy communities to encourage their engagement. This works describes strategies for an energy management system adapted to energy community developers whose business model consists in installing, owning and managing energy assets (such as photovoltaic panels and batteries) in its own facilities and in the facilities of those energy community members able and willing to provide them, to sell the locally produced energy for self-consumption in the energy community.

Abstract
Discerning between quantum and classical correlations is of great importance. Bell polytopes are well established as a fundamental tool for such a purpose. In this paper, we extend this line of inquiry by applying resource theory within the context of network scenarios, to a Quantum Key Distribution (QKD) protocol, BBM92. To achieve this, we consider the causal structure P3 to describe the protocol, and we aim to develop useful statistical tests to assess it. Our objectives are twofold: firstly, to utilise the underlying causal structure of the QKD protocol to produce a geometrical analysis of the resulting nonconvex polytope, with a focus on the classical behaviours, and secondly to devise a test within this framework to evaluate the distance between any two behaviours within the generated polytope. This approach offers a unique perspective, linking deviations from expected behaviour directly to the quality of the quantum resource involved or the residual nonclassicality in protocol execution.

Abstract
The autonomous navigation of unmanned ground vehicles (UGVs) in unstructured environments, such as agricultural or forestry settings, has been the subject of extensive research by various investigators. The navigation capability of a UGV in unstructured environments requires considering numerous factors, including the quality of data reception that allows reliable interpretation of what the UGV perceives in a given environment, as well as the use these data to control the UGV's navigation. This article aims to study different PID control algorithms to enable autonomous navigation on a robotic platform. The robotic platform consists of a forestry tractor, used for forest cleaning tasks, which was converted into a UGV through the integration of sensors. Using sensor data, the UGV's position and orientation are obtained and utilized for navigation by inputting these data into a PID control algorithm. The correct choice of PID control algorithm involved the study, analysis, and implementation of different controllers, leading to the conclusion that the Vector Field control algorithm demonstrated better performance compared to the others studied and implemented in this paper.

Abstract
The business models (BM) for renewable energy communities (REC) are often based on their promoters being the sole or primary investors in energy assets, such as photovoltaic panels (PV) and battery energy storage systems (BESS), operating these assets centrally, and selling the locally produced energy to the REC members. This research addresses the computation of fixed local energy prices that the REC developer may apply under the optimal operation of the energy assets to maximize its revenues, while guaranteeing that all REC members benefit from belonging to the REC. We do this from two perspectives, depending on who operates the storage systems: i) maximizing the investor's benefits and ii) minimizing the REC cost by maximizing its self-consumption, ensuring maximization of the energy sold by the REC promoter/investor. The optimization framework includes energy production and demand balance constraints, peak load limitations, and constraints coming from the Portuguese regulatory framework. It also considers the opportunity costs of the members for buying the energy deficit from the grid or selling the energy surplus to the grid.

Abstract