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- Oportunidades para o IPCB no Programa de Recuperação e ResiliênciaPublication . Marques, PauloO Programa de Recuperação e Resiliência (PRR), apresentado à Comissão Europeia pelo Governo, enquadra-se no mecanismo extraordinário NEXT GENERATION EU criado em resposta à crise causada pela pandemia COVID19 e que será utilizado pela primeira vez na história da União Europeia. O PRR é um programa com um período de execução até 2026, e vai implementar um conjunto de investimentos no valor de 16,4 mil M€. Durante os próximos seis anos o PRR fará fluir meios numa dimensão sem precedentes para a modernização e o desenvolvimento económico e social de Portugal. O PRR está organizado em 3 dimensões estruturantes: a Resiliência, a Transição Climática e a Transição Digital, num total de 20 componentes e 83 investimentos.
- Bin-picking solution for randomly placed automotive connectors based on machine learning techniquesPublication . Torres, Pedro; Arents, Janis; Marques, Hugo; Marques, PauloThis paper presents the development of a bin-picking solution based on low-cost vision systems for the manipulation of automotive electrical connectors using machine learning techniques. The automotive sector has always been in a state of constant growth and change, which also implies constant challenges in the wire harnesses sector, and the emerging growth of electric cars is proof of this and represents a challenge for the industry. Traditionally, this sector is based on strong human work manufacturing and the need arises to make the digital transition, supported in the context of Industry 4.0, allowing the automation of processes and freeing operators for other activities with more added value. Depending on the car model and its feature packs, a connector can interface with a different number of wires, but the connector holes are the same. Holes not connected with wires need to be sealed, mainly to guarantee the tightness of the cable. Seals are inserted manually or, more recently, through robotic stations. Due to the huge variety of references and connector configurations, layout errors sometimes occur during seal insertion due to changed references or problems with the seal insertion machine. Consequently, faulty connectors are dumped into boxes, piling up different types of references. These connectors are not trash and need to be reused. This article proposes a bin-picking solution for classification, selection and separation, using a two-finger gripper, of these connectors for reuse in a new operation of removal and insertion of seals. Connectors are identified through a 3D vision system, consisting of an Intel RealSense camera for object depth information and the YOLOv5 algorithm for object classification. The advantage of this approach over other solutions is the ability to accurately detect and grasp small objects through a low-cost 3D camera even when the image resolution is low, benefiting from the power of machine learning algorithms.
- O 5G em tempos de pandemia.Publication . Marques, PauloUma pessoa gastaria 82 anos de vida para visualizar todos os vídeos que são publicados no Youtube durante um único dia. O tráfego gerado pelos telemóveis cresce duma forma continuada devido às redes sociais e à partilha de vídeos na Internet. As redes de telecomunicações são a espinha dorsal da sociedade da informação em que vivemos. O fenómeno das redes sociais e do Youtube só foi possível graças à quarta geração móvel (4G), disponível a partir do ano 2010. Com o 4G foi possível atingir velocidades médias de acesso à Internet de 50 Mbit/s, na maior parte das zonas urbanas, o que permite, uma qualidade de experiência na partilha de conteúdos multimédia quase instantânea.
- Pedestrian detection with lidar technology in smart-city deployments - challenges and recommendationsPublication . Torres, Pedro; Marques, Hugo; Marques, PauloAbstract: This paper describes a real case implementation of an automatic pedestrian-detection solution, implemented in the city of Aveiro, Portugal, using affordable LiDAR technology and open, publicly available, pedestrian-detection frameworks based on machine-learning algorithms. The presented solution makes it possible to anonymously identify pedestrians, and extract associated information such as position, walking velocity and direction in certain areas of interest such as pedestrian crossings or other points of interest in a smart-city context. All data computation (3D point-cloud processing) is performed at edge nodes, consisting of NVIDIA Jetson Nano and Xavier platforms, which ingest 3D point clouds from Velodyne VLP-16 LiDARs. High-performance real-time computation is possible at these edge nodes through CUDA-enabled GPU-accelerated computations. The MQTT protocol is used to interconnect publishers (edge nodes) with consumers (the smartcity platform). The results show that using currently affordable LiDAR sensors in a smart-city context, despite the advertising characteristics referring to having a range of up to 100 m, presents great challenges for the automatic detection of objects at these distances. The authors were able to efficiently detect pedestrians up to 15 m away, depending on the sensor height and tilt. Based on the implementation challenges, the authors present usage recommendations to get the most out of the used technologies.