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View article: Crack detection in powder compacts using machine learning models
Crack detection in powder compacts using machine learning models Open
Purpose Cracks in powder metallurgy (PM) components, being a common problem, pose significant manufacturing challenges but are detrimental to be detected as they affect the material’s mechanical properties. To detect these cracks, non-dest…
View article: A novel strain-dependent FEM model for metal powder compaction using Code_Aster
A novel strain-dependent FEM model for metal powder compaction using Code_Aster Open
This study proposes a novel finite element model for metal powder compaction using the open-source software Salome-Meca, employing Code Aster as a solver. The developed model incorporates a variable elastic modulus that changes as a functi…
View article: Dynamic emotion intensity estimation from physiological signals facilitating interpretation via appraisal theory
Dynamic emotion intensity estimation from physiological signals facilitating interpretation via appraisal theory Open
Appraisal models, such as the Scherer’s Component Process Model (CPM), represent an elegant framework for the interpretation of emotion processes, advocating for computational models that capture emotion dynamics. Today’s emotion recogniti…
View article: Determination of Crack Limits in Sinter Components by Compaction Process Performance Analysis
Determination of Crack Limits in Sinter Components by Compaction Process Performance Analysis Open
Cracks in sinter component production are a significant concern in the field of powder metallurgy, and predicting and avoiding them is crucial for ensuring the quality and reliability of the final products. This study aims to contribute to…
View article: ALPINE: a climbing robot for operations in mountain environments
ALPINE: a climbing robot for operations in mountain environments Open
Mountain slopes are perfect examples of harsh environments in which humans are required to perform difficult and dangerous operations such as removing unstable boulders, dangerous vegetation or deploying safety nets. A good replacement for…
View article: Neural-network-based automatic trajectory adaptation for quality characteristics control in powder compaction
Neural-network-based automatic trajectory adaptation for quality characteristics control in powder compaction Open
Future manufacturing systems will have to become more intelligent to be able to guarantee a constantly high quality of products while simultaneously reducing labor-intensive quality-assurance tasks to address the shortage in workforce. In …
View article: Automatic trajectory adaptation for the control of quality characteristics in a powder compaction process
Automatic trajectory adaptation for the control of quality characteristics in a powder compaction process Open
The manufacturing process of sintered components requires the compaction of powder in a rigid die and the sintering of the resulting green parts. To produce green parts of the same constant quality over a long period of time, regular quali…
View article: CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments
CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments Open
Rescue missions in mountain environments are hardly achievable by standard legged robots—because of the high slopes—or by flying robots—because of limited payload capacity. We present a concept for a rope-aided climbing robot which can neg…
View article: A Novel Mirror Neuron Inspired Decision-Making Architecture for Human–Robot Interaction
A Novel Mirror Neuron Inspired Decision-Making Architecture for Human–Robot Interaction Open
Inspired by the role of mirror neurons and the importance of predictions in joint action, a novel decision-making structure is proposed, designed and tested for both individual and dyadic action. The structure comprises models representing…
View article: NILRNN: A Neocortex-Inspired Locally Recurrent Neural Network for Unsupervised Feature Learning in Sequential Data
NILRNN: A Neocortex-Inspired Locally Recurrent Neural Network for Unsupervised Feature Learning in Sequential Data Open
Unsupervised feature learning refers to the problem of learning useful feature extraction functions from unlabeled data. Despite the great success of deep learning networks in this task in recent years, both for static and for sequential d…
View article: Estimation of Mass and Lengths of Sintered Workpieces Using Machine Learning Models
Estimation of Mass and Lengths of Sintered Workpieces Using Machine Learning Models Open
Powder Metallurgy (PM) is the branch of Metallurgy that deals with the design/production of near net-shaped sintered workpieces with different shapes and characteristics. The produced sintered workpieces are used in automotive, aviation, a…
View article: A Decision-Making Architecture for Human-Robot Collaboration: Model Transferability
A Decision-Making Architecture for Human-Robot Collaboration: Model Transferability Open
In this paper, we aim to demonstrate the potential for wider-ranging capabilities and ease of transferability of our recently developed decision-making architecture for human-robot collaboration. To this end, a somewhat related but differe…
View article: CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments
CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments Open
Rescue missions in mountain environments are hardly achievable by standard legged robots-because of the high slopes-or by flying robots-because of limited payload capacity. We present a concept for a rope-aided climbing robot which can neg…
View article: Wood Products Manufacturing Optimization: A Survey
Wood Products Manufacturing Optimization: A Survey Open
The wood industry is a basic industry supplying primary materials to produce a wide range of products. The wood processing in sawmills bridges the transformation flow of raw materials to final products using machinery. Over the last decade…
View article: Model Predictive Control-Based Reinforcement Learning Using Expected Sarsa
Model Predictive Control-Based Reinforcement Learning Using Expected Sarsa Open
Recent studies have shown the potential of Reinforcement Learning (RL) algorithms in tuning the parameters of Model Predictive Controllers (MPC), including the weights of the cost function and unknown parameters of the MPC model. However, …
View article: Activity, Plan, and Goal Recognition: A Review
Activity, Plan, and Goal Recognition: A Review Open
Recognizing the actions, plans, and goals of a person in an unconstrained environment is a key feature that future robotic systems will need in order to achieve a natural human-machine interaction. Indeed, we humans are constantly understa…