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Now showing items 1-10 of 45
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2020)
Surface electromyography (sEMG) provides an intuitive and non-invasive interface from which to control machines. However, preserving the myoelectric control system’s performance over multiple days is challenging, due to ...
(Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2016)
Inspired by animals’ ability to learn and adapt to changes in their environment during life, hybrid evolutionary algorithms have been developed and successfully applied in a number of research areas. This paper explores ...
(Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2017)
Evolving robot morphologies implies the need for lifetime learning so that newborn robots can learn to manipulate their bodies. An individual’s morphology will obviously combine traits of all its parents; it must adapt its ...
(Doctoral thesis / Doktoravhandling, 2008)
Evolvable hardware (EHW) is a method where hardware is designed and/or modified automatically by optimization algorithms called evolutionary algorithms (EAs). The results so far are promising but somewhat limited partly ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2019)
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2019)
Collaborative robots are becoming more common on factory floors as well as regular environments, however, their safety still is not a fully solved issue. Collision detection does not always perform as expected and collision ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2019)
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 robust enough to meet this challenge. ...
(Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2019)
Overcoming robotics challenges in the real world requires resilient control systems capable of handling a multitude of environments and unforeseen events. Evolutionary optimization using simulations is a promising way to ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2019)
The complexity of a legged robot’s environment or task can inform how specialised its gait must be to ensure success. Evolving specialised robotic gaits demands many evaluations—acceptable for computer simulations, but not ...
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2019)
We study evolutionary robot systems where not only the robot brains but also the robot bodies are evolvable. Such systems need to include a learning period right after ‘birth’ to acquire a controller that fits the newly ...