63 citations · 185 across the 37 of their papers we have counts for
8 papers · 1 filter
Transfer Learning for Unseen Robot Detection and Joint Estimation on a Multi-Objective Convolutional Neural Network
Justinas Miseikis, Inka Brijacak, Saeed Yahyanejad +3
A significant problem of using deep learning techniques is the limited amount of data available for training. There are some datasets available for the popular problems like item r…
Multi-Objective Convolutional Neural Networks for Robot Localisation and 3D Position Estimation in 2D Camera Images
Justinas Miseikis, Inka Brijacak, Saeed Yahyanejad +3
The field of collaborative robotics and human-robot interaction often focuses on the prediction of human behaviour, while assuming the information about the robot setup and configu…
Real-World Evolution Adapts Robot Morphology and Control to Hardware Limitations
Tønnes F. Nygaard, Charles P. Martin, Eivind Samuelsen +2
For robots to handle the numerous factors that can affect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of the…
Exploring Mechanically Self-Reconfiguring Robots for Autonomous Design
Tønnes F. Nygaard, Charles P. Martin, Jim Torresen +1
Evolutionary robotics has aimed to optimize robot control and morphology to produce better and more robust robots. Most previous research only addresses optimization of control, an…
Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing
Tønnes F. Nygaard, Charles P. Martin, Jim Torresen +1
If robots are to become ubiquitous, they will need to be able to adapt to complex and dynamic environments. Robots that can adapt their bodies while deployed might be flexible and…
Multi-objective Analysis of MAP-Elites Performance
Eivind Samuelsen, Kyrre Glette
In certain complex optimization tasks, it becomes necessary to use multiple measures to characterize the performance of different algorithms. This paper presents a method that comb…
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
Ulysse Côté-Allard, Cheikh Latyr Fall, Alexandre Drouin +5
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of…
Robot Localisation and 3D Position Estimation Using a Free-Moving Camera and Cascaded Convolutional Neural Networks
Justinas Miseikis, Patrick Knobelreiter, Inka Brijacak +4
Many works in collaborative robotics and human-robot interaction focuses on identifying and predicting human behaviour while considering the information about the robot itself as g…