Abstract
Object identification, such as tree trunk detection, is fundamental for forest robotics. Intelligent vision systems are of paramount importance in order to improve robotic perception, thus enhancing the autonomy of forest robots. To that purpose, this paper presents three contributions: an open dataset of 5325 annotated forest images; a tree trunk detection Edge AI benchmark between 13 deep learning models evaluated on four edge-devices (CPU, TPU, GPU and VPU); and a tree trunk mapping experiment using an OAK-D as a sensing device. The results showed that YOLOR was the most reliable trunk detector, achieving a maximum F1 score around 90% while maintaining high scores for different confidence levels; in terms of inference time, YOLOv4 Tiny was the fastest model, attaining 1.93 ms on the GPU. YOLOv7 Tiny presented the best trade-off between detection accuracy and speed, with average inference times under 4 ms on the GPU considering different input resolutions and at the same time achieving an F1 score similar to YOLOR. This work will enable the development of advanced artificial vision systems for robotics in forestry monitoring operations.

Abstract
Scientific advances in recent decades have provided universal access to a variety of new digital technologies. These technologies are used by the vast majority of today's university students. Therefore, the incorporation of innovative methods and technologies is a must in order to actively engage students in the learning process. In this paper, a selection of techniques that can be considered 'outside of the box' are examined in the context of the application of teaching/learning methods in control engineering and industrial automation education. © 2022 IEEE.

Abstract
The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.

Abstract
The Multiple Traveling Salesman Problem (mTSP) is an interesting combinatorial optimization problem due to its numerous real-life applications. It is a problem where m salesmen visit a set of n cities so that each city is visited once. The primary purpose is to minimize the total distance traveled by all salesmen. This paper presents a hybrid approach called GABC-LS that combines an evolutionary algorithm with the swarm intelligence optimization ideas and a local search method. The proposed approach was tested on three instances and produced some better results than the best-known solutions reported in the literature.

Abstract

Abstract
The paper presents an application of the new control paradigm, which is based on process moments, to a model of a DC motor. The basis of the new control paradigm is that it eliminates the process transfer function within the closed loop, as it estimates the final steady-state value of the process output and compares it with the reference signal. As a result, the closed loop response is much more stable and generally without overshoots. This property makes it suitable for application to motor-driven processes where overshoots is undesirable. It was shown that the control method provides very stable closed-loop responses even when the actual motor and the model parameters differ. It was also shown that the proposed method can be applied to constrained systems as the anti-windup protection is implicitly embedded in the control solution. © 2025 IEEE.