Recent Submissions

  • Enhanced plastic recycling using RGB+depth fusion with massFaster and massMask R-CNN 

    Diaz-Romero, Dillam; Zaplana Agut, Isiah; Van den Eynde, Simon; Sterkens, Wouter; Goedemé, Toon; Peeters, Jef R.
    Conference report
    Open Access
    The rapid increase in waste generation from electrical and electronic equipment (WEEE) has created the need for more advanced sensor-based systems to sort this complex type of waste. Therefore, this study proposes a method ...
  • A novel strategy for balancing the workload of industrial lines based on a genetic algorithm 

    Zaplana Agut, Isiah; Cepolina, Emanuela; Lucia, Oronzo; Gagliardi, Roberto; Baizid, Khelifa; D'Imperio, MariaPaola; Cannella, Ferdinando
    Conference report
    Open Access
    One major problem in industrial automation is the workload balancing problem. It consists of making the robots or, more generally, the machines, involved in the assembly process to work exactly the same, either by picking ...
  • Classification of aluminum scrap by laser induced breakdown spectroscopy (LIBS) and RGB + D image fusion using deep learning approaches 

    Diaz-Romero, Dillam; Van den Eynde, Simon; Zaplana Agut, Isiah; Sterkens, Wouter; Goedemé, Toon; Peeters, Jef R. (2023-03)
    Article
    Restricted access - publisher's policy
    Integrating multi-sensor systems to sort and monitor complex waste streams is one of the most recent innovations in the recycling industry. The complementary strengths of Laser-Induced Breakdown Spectroscopy (LIBS) and ...
  • Deep learning regression for quantitative LIBS analysis 

    Van den Eynde, Simon; Diaz-Romero, Dillam; Zaplana Agut, Isiah; Peeters, Jef R. (2023-02)
    Article
    Restricted access - publisher's policy
    One of the most promising innovation strategies for sorting and recycling post-consumer aluminium scrap is using quantitative Laser-Induced Breakdown Spectroscopy (LIBS) analysis. However, existing methods to estimate ...
  • Simultaneous mass estimation and class classification of scrap metals using deep learning 

    Diaz-Romero, Dillam; Van den Eynde, Simon; Sterkens, Wouter; Engelen, Bart; Zaplana Agut, Isiah; Dewulf, Wim; Goedemé, Toon; Peeters, Jef R. (2022-06)
    Article
    Open Access
    While deep learning has helped improve the performance of classification, object detection, and segmentation in recycling, its potential for mass prediction has not yet been explored. Therefore, this study proposes a system ...
  • You Only Demanufacture Once (YODO): WEEE retrieval using unsupervised learning 

    Zhou, Chuangchuang; Sterkens, Wouter; Diaz-Romero, Dillam; Zaplana Agut, Isiah; Peeters, Jef R. (2023-03)
    Article
    Restricted access - publisher's policy
    Recent developments in robotic demanufacturing raise the potential to increase the cost-efficiency of recycling and recovering resources from Waste of Electrical and Electronic Equipment (WEEE). However, the industrial ...
  • Closed-form solutions for the inverse kinematics of serial robots using conformal geometric algebra 

    Zaplana Agut, Isiah; Hadfield, Hugo; Lasenby, Joan (2022-07)
    Article
    Restricted access - publisher's policy
    This work addresses the inverse kinematics of serial robots using conformal geometric algebra. Classical approaches include either the use of homogeneous matrices, which entails high computational cost and execution time, ...
  • Singularities of serial robots: identification and distance computation using geometric algebra 

    Zaplana Agut, Isiah; Hadfield, Hugo; Lasenby, Joan (Multidisciplinary Digital Publishing Institute (MDPI), 2022-06-15)
    Article
    Open Access
    The singularities of serial robotic manipulators are those configurations in which the robot loses the ability to move in at least one direction. Hence, their identification is fundamental to enhance the performance of ...
  • Efficient and robust trajectory generation for robotic manipulators 

    Ruiz Celada, Oriol; Palomo Avellaneda, Leopold; Suárez Feijóo, Raúl; Rosell Gratacòs, Jan (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference lecture
    Open Access
    This paper describes a procedure to generate valid robot trajectories for a given sequence of points defining a geometric path, which is a quite frequent output of many robot motion planners. The proposed approach takes ...
  • Edge computing in autonomous and collaborative assembly lines 

    Urbaniak, Dominik; Rosell Gratacòs, Jan; Suárez Feijóo, Raúl (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Industry 4.0 demands interconnected production lines that consist of modular assets. Recent advances of wireless communication technologies allow a large connectivity of devices and approach the performance of wireline ...
  • Task space vector field guiding for motion planning 

    Urra González, Fernando; Rosell Gratacòs, Jan; Suárez Feijóo, Raúl (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    The article deals with the problem of planning in the task space in the presence of vector fields, while verifying and validating the constraints in the configuration space. The proposed approach, called the Task Space ...
  • Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches 

    Diaz-Romero, Dillam; Van den Eynde, Simon; Sterkens, Wouter; Zaplana Agut, Isiah; Goedemé, Toon; Peeters, Jef R. (2022-10)
    Article
    Restricted access - publisher's policy
    In the recycling industry, the use of deep spectral convolutional networks for the purpose of material classification and composition estimation is still limited, despite the great opportunities of these techniques. In ...

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