Understanding and respecting personal space preferences is essential for socially assistive robots designed for older adult users. This work introduces and evaluates a novel personalized context-aware method for modeling users’ proxemics preferences during human-robot interactions. Using an interactive augmented reality interface, we collected a set of user-preferred distances … [Read more...] about An Interactive Augmented Reality Interface for Personalized Proxemics Modeling: Comfort and Human–Robot Interactions
Data models
A Digital Twin of the Research Vessel Gunnerus for Lifecycle Services: Outlining Key Technologies
Digitalization has become a key aspect of making maritime industries more innovative, efficient, and fit for future operations. One of the most attractive aspects is the concept of digital twins , which refers to digital replicas of physical assets, processes, and systems that can be used as advanced tools for design, operation, and maintenance. This article introduces the … [Read more...] about A Digital Twin of the Research Vessel Gunnerus for Lifecycle Services: Outlining Key Technologies
Mastering the Complex Assembly Task With a Dual-Arm Robot: A Novel Reinforcement Learning Method
Deep reinforcement learning (DRL) has achieved great success across multiple fields; however, in the field of robot control, the acquisition of large amounts of motion data from real robots is challenging. In this work, an algorithm is proposed to train a neural network model with a large amount of data in a simulated environment and then transfer the model to the real … [Read more...] about Mastering the Complex Assembly Task With a Dual-Arm Robot: A Novel Reinforcement Learning Method
Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
Automatic defect inspection is an important application for the development of smart factories in the era of Industry 4.0. It gathers data from production lines to train a model to automatically recognize certain types of defects. However, the defect types may vary in the production process, and it is difficult for the old model to adapt to new types of defects directly. … [Read more...] about Toward Lifelong Learning for Industrial Defect Classification: A Proposed Framework
FEA-Based Inverse Kinematic Control: Hyperelastic Material Characterization of Self-Healing Soft Robots
Recent advances in soft continuum robots revealed the need for accurate models, required to develop advanced control strategies. In this article, a general methodology is presented that allows to create an accurate inverse kinematic control based on hyperelastic models, fitted on mechanical material properties. This methodology is based on finite element analysis (FEA) and … [Read more...] about FEA-Based Inverse Kinematic Control: Hyperelastic Material Characterization of Self-Healing Soft Robots
