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A Framework on Division of Work Tasks between Humans and Robots in the Home 
Saplacan, Diana; Herstad, Jo; Tørresen, Jim; Pajalic, Zada (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2020)
This paper analyzes work activity in the home, e.g., cleaning, performed by two actors, a human and a robot. Nowadays, there are attempts to automate this activity through the use of robots. However, the activity of cleaning, ...
Towards Playing in the 'Air': Modeling Motion-Sound Energy Relationships in Electric Guitar Performance Using Deep Neural Networks 
Erdem, Cagri; Lan, Qichao; Fuhrer, Julian; Martin, Charles Patrick; Tørresen, Jim; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2020)
In acoustic instruments, sound production relies on the interaction between physical objects. Digital musical instruments, on the other hand, are based on arbitrarily designed action--sound mappings. This paper describes ...
Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls 
Jakobsen, Petter; Garcia-Ceja, Enrique; Riegler, Michael; Stabell, Lena Antonsen; Nordgreen, Tine; Tørresen, Jim; Fasmer, Ole Bernt; Ødegaard, Ketil Joachim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2020)
Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner ...
Guiding Neuroevolution with Structural Objectives 
Ellefsen, Kai Olav; Huizinga, Joost; Tørresen, Jim (Journal article / Tidsskriftartikkel / SubmittedVersion, 2020)
The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally adapted to a given task can be explored. Guiding such neuroevolution ...
Additive manufacturing of laminar flow cells for single-molecule experiments 
Ahmadi, Arash; Till, Katharina; Hafting, Yngve; Schuttpelz, Mark; Bjørås, Magnar; Glette, Kyrre; Tørresen, Jim; Rowe, Alexander D.; Dalhus, Bjørn (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2019)
A microfluidic laminar flow cell (LFC) forms an indispensable component in single-molecule experiments, enabling different substances to be delivered directly to the point under observation and thereby tightly controlling ...
RaveForce: A Deep Reinforcement Learning Environment for Music 
Lan, Qichao; Tørresen, Jim; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
RaveForce is a programming framework designed for a computational music generation method that involves audio sample level evaluation in symbolic music representation generation. It comprises a Python module and a SuperCollider ...
Facial Expression Recognition Using Robust Local Directional Strength Pattern Features and Recurrent Neural Network 
Rokkones, Anders Skibeli; Uddin, Md Zia; Tørresen, Jim (Book chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2019)
This work proposes a novel facial expression recognition approach to contribute to better human-machine interactions. To do that, edge features in facial expression images are combined with a recurrent neural network (RNN) ...
Parameterized Melody Generation with Autoencoders and Temporally-Consistent Noise 
Weber, Aline; Alegre, Lucas N.; Tørresen, Jim; Castro da Silva, Bruno (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
We introduce a machine learning technique to autonomously generate novel melodies that are variations of an arbitrary base melody. These are produced by a neural network that ensures that (with high probability) the melodic ...
Comparison of Probabilistic Models and Neural Networks on Prediction of Home Sensor Events 
Casagrande, Flavia Dias; Tørresen, Jim; Zouganeli, Evi (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2019)
We present results and comparative analysis on the prediction of sensor events in a smart home environment with a limited number of binary sensors. We apply two probabilistic methods, namely Sequence Prediction via Enhanced ...
Multi-Query Motion Planning in Uncertain Spaces: Incremental Adaptive Randomized Roadmaps 
Khaksar, Weria; Uddin, Md Zia; Tørresen, Jim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2019)
Sampling-based motion planning is a powerful tool in solving the motion planning problem for a variety of different robotic platforms. As its application domains grow, more complicated planning problems arise that challenge ...
Data Driven Analysis of Tiny Touchscreen Performance with MicroJam 
Martin, Charles Patrick; Tørresen, Jim (Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2019)
The widespread adoption of mobile devices, such as smartphones and tablets, has made touchscreens a common interface for musical performance. While new mobile music instrument have been investigated from design and user ...
An Interactive Musical Prediction System with Mixture Density Recurrent Neural Networks 
Martin, Charles Patrick; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
This paper is about creating digital musical instruments where a predictive neural network model is integrated into the interactive system. Rather than predicting symbolic music (e.g., MIDI notes), we suggest that predicting ...
Two-Stage Transfer Learning for Heterogeneous Robot Detection and 3D Joint Position Estimation in a 2D Camera Image Using CNN 
Miseikis, Justinas; Brijacak, Inka; Yahyanejad, Saeed; Glette, Kyrre; Elle, Ole Jacob; Tørresen, Jim (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 ...
Generating Convincing Harmony Parts with Simple Long Short-Term Memory Networks 
Faitas, Andrei; Baumann, Synne Engdahl; Næss, Torgrim Rudland; Tørresen, Jim; Martin, Charles Patrick (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
Generating convincing music via deep neural networks is a challenging problem that shows promise for many applications including interactive musical creation. One part of this challenge is the problem of generating convincing ...
Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing 
Nygaard, Tønnes Frostad; Martin, Charles Patrick; Tørresen, Jim; Glette, Kyrre (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. ...
Predicting Sensor Events, Activities, and Time of Occurrence Using Binary Sensor Data From Homes With Older Adults 
Casagrande, Flavia Dias; Tørresen, Jim; Zouganeli, Evi (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2019)
We present a comprehensive study of state-of-the-art algorithms for the prediction of sensor events and activities of daily living in smart homes. Data have been collected from eight smart homes with real users and 13-17 ...
Incremental Adaptive Probabilistic Roadmaps for Mobile Robot Navigation under Uncertain Condition 
Khaksar, Weria; Uddin, Md Zia; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
As the application domains of sampling-based motion planning grow, more complicated planning problems arise that challenge the functionality of these planners. One of the main challenges in the implementation of a ...
Moving with Style: Classifying Human and Robot Movement at Home 
Schulz, Trenton Wade; Herstad, Jo; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2018)
A robot moving in the home is a new experience for most people. Classifying the different ways that humans and robots move together can help in designing interactions. In this paper, we first put robots’ movements into two ...
Robot Localisation and 3D Position Estimation Using a Free-Moving Camera and Cascaded Convolutional Neural Networks 
Miseikis, Justinas; Knobelreiter, Patrick; Brijacak, Inka; Yahyanejad, Saeed; Glette, Kyrre; Elle, Ole Jacob; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
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 given. This can be the case when sensors ...
Multi-Objective Convolutional Neural Networks for Robot Localisation and 3D Position Estimation in 2D Camera Images 
Miseikis, Justinas; Brijacak, Inka; Yahyanejad, Saeed; Glette, Kyrre; Elle, Ole Jacob; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
The field of collaborative robotics and humanrobot interaction often focuses on the prediction of human behaviour, while assuming the information about the robot setup and configuration being known. This is often the case ...
Ambient Sensors for Elderly Care and Independent Living: A Survey 
Uddin, Md Zia; Khaksar, Weria; Tørresen, Jim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2018)
Elderly care at home is a matter of great concern if the elderly live alone, since unforeseen circumstances might occur that affect their well-being. Technologies that assist the elderly in independent living are essential ...
Transfer Learning for Unseen Robot Detection and Joint Estimation on a Multi-Objective Convolutional Neural Network 
Miseikis, Justinas; Brijacak, Inka; Yahyanejad, Saeed; Glette, Kyrre; Elle, Ole Jacob; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
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 recognition and classification or self-driving ...
Real-world evolution adapts robot morphology and control to hardware limitations 
Nygaard, Tønnes Frostad; Martin, Charles Patrick; Samuelsen, Eivind; Tørresen, Jim; Glette, Kyrre (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
For robots to handle the numerous factors that can afect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of these issues by automatically optimizing a ...
Classifying Human and Robot Movement at Home and Implementing Robot Movement Using the Slow In, Slow Out Animation Principle 
Schulz, Trenton Wade; Herstad, Jo; Tørresen, Jim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2018)
We examine how robot movement can help human-robot interaction in the context of a robot helping people over 60-years old at home. Many people are not familiar with a robot moving in their home. We present four movement ...
A Review of Future and Ethical Perspectives of Robotics and AI 
Tørresen, Jim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2018)
In recent years, there has been increased attention on the possible impact of future robotics and AI systems. Prominent thinkers have publicly warned about the risk of a dystopian future when the complexity of these systems ...
Breaking the speed limit with multimode fast scanning of DNA by Endonuclease V 
Ahmadi, Arash; Rosnes, Ida; Blicher, Pernille; Diekmann, Robin; Schuttpelz, Mark; Glette, Kyrre; Tørresen, Jim; Bjørås, Magnar; Dalhus, Bjørn; Rowe, Alexander D. (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2018)
Recognizing Bedside Events Using Thermal and Ultrasonic Readings 
Danielsen, Asbjørn; Tørresen, Jim (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2017)
Falls in homes of the elderly, in residential care facilities and in hospitals commonly occur in close proximity to the bed. Most approaches for recognizing falls use cameras, which challenge privacy, or sensor devices ...
MicroJam: An App for Sharing Tiny Touch-Screen Performances 
Martin, Charles Patrick; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
MicroJam is a mobile app for sharing tiny touch-screen performances. Mobile applications that streamline creativity and social interaction have enabled a very broad audience to develop their own creative practices. While ...
Exploring Social Mobile Music with Tiny Touch-Screen Performances 
Martin, Charles Patrick; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
Touch-screen musical performance has become commonplace since the widespread adoption of mobile devices such as smartphones and tablets. However, mobile digital musical instruments are rarely designed to emphasise collaborative ...
Funky Sole Music: Gait Recognition and Adaptive Mapping 
Nymoen, Kristian; Song, Sichao; Hafting, Yngve; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2014)
We present Funky Sole Music, a musical interface employing a sole embedded with three force sensitive resistors in combination with a novel algorithm for continuous movement classification. A heuristics-based music engine ...
PheroMusic: Navigating a Musical Space for Active Music Experiences 
Nymoen, Kristian; Chandra, Arjun; Glette, Kyrre Harald; Tørresen, Jim; Voldsund, Arve; Jensenius, Alexander Refsum (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2014)
We consider the issue of how a flexible musical space can be manipulated by users of an active music system. The musical space is navigated within by selecting transitions between different sections of the space. We take ...
The Challenge of Decentralised Synchronisation in Interactive Music Systems 
Nymoen, Kristian; Chandra, Arjun; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2013)
Synchronisation is an important part of collaborative music systems, and with such systems implemented on mobile devices, the implementation of algorithms for synchronisation without central control becomes increasingly ...
Analyzing correspondence between sound objects and body motion 
Nymoen, Kristian; Godøy, Rolf Inge; Jensenius, Alexander Refsum; Tørresen, Jim (Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2013)
Links between music and body motion can be studied through experiments called sound-tracing. One of the main challenges in such research is to develop robust analysis techniques that are able to deal with the multidimensional ...
EasyPR – an Easy Usable Open-Source PR System 
Koch, Dirk; Beckhoff, Christian; Tørresen, Jim; Wold, Alexander (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2013)
In this paper, we present an open source partial reconfiguration (PR) system which is designed for portability and usability serving as a reference for engineers and students interested in using the advanced reconfiguration ...
Development and evaluation of a ZigFlea-based wireless transceiver board for CUI32 
Tørresen, Jim; Hauback, Øyvind N.; Overholt, Dan; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2012)
We present a new wireless transceiver board for the CUI32 sensor interface, aimed at creating a solution that is flexible, reliable, and with little power consumption. Communication with the board is based on the ZigFlea ...
A Statistical Approach to Analyzing Sound Tracings 
Nymoen, Kristian; Tørresen, Jim; Godøy, Rolf Inge; Jensenius, Alexander Refsum (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2012)
This paper presents an experiment on sound tracing, meaning an experiment on how people relate motion to sound. 38 participants were presented with 18 short sounds, and instructed to move their hands in the air while acting ...
Enabling Participants to Play Rhythmic Solos Within a Group via Auctions 
Chandra, Arjun; Nymoen, Kristian; Voldsund, Arve; Jensenius, Alexander Refsum; Glette, Kyrre Harald; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2012)
The paper presents the interactive music system SoloJam, which allows a group of participants with little or no musical training to effectively play together in a ``band-like'' setting. It allows the participants to take ...
Comparing Motion Data from an iPod Touch to a High-End Optical Infrared Marker-Based Motion Capture System 
Nymoen, Kristian; Voldsund, Arve; Skogstad, Ståle Andreas van Dorp; Jensenius, Alexander Refsum; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2012)
The paper presents an analysis of the quality of motion data from an iPod Touch (4th gen.). Acceleration and orientation data derived from internal sensors of an iPod is compared to data from a high end optical infrared ...
Classifying Music-Related Actions 
Godøy, Rolf Inge; Jensenius, Alexander Refsum; Voldsund, Arve; Glette, Kyrre Harald; Høvin, Mats Erling; Nymoen, Kristian; Skogstad, Ståle Andreas van Dorp; Tørresen, Jim (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2012)
Our research on music-related actions is based on the conviction that sensations of both sound and body motion are inseparable in the production and perception of music. The expression "musicrelated actions" is here used ...
Can Run-time Reconfigurable Hardware be more Accessible? 
Tørresen, Jim; Koch, Dirk (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2011)
In this paper, a new project named Context Switching Reconfigurable Hardware for Communication Systems (COSRECOS) is introduced. The project started autumn 2009 and consists of applying reconfigurable hardware technology ...
fourMs, University of Oslo Lab Report 
Jensenius, Alexander Refsum; Glette, Kyrre Harald; Godøy, Rolf Inge; Høvin, Mats Erling; Nymoen, Kristian; Skogstad, Ståle Andreas van Dorp; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2010)
The paper reports on the development and activities in the recently established fourMs lab (Music, Mind, Motion, Machines) at the University of Oslo, Norway. As a meeting place for researchers in music and informatics, the ...
Searching for Cross-Individual Relationships between Sound and Movement Features using an SVM Classi er 
Nymoen, Kristian; Jensenius, Alexander Refsum; Tørresen, Jim; Glette, Kyrre Harald; Skogstad, Ståle Andreas van Dorp (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2010)
In this paper we present a method for studying relationships between features of sound and features of movement. The method has been tested by carrying out an experiment with people moving an object in space along with ...
Wireless Sensor Data Collection based on ZigBee Communication 
Tørresen, Jim; Renton, Eirik; Jensenius, Alexander Refsum (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2010)
This paper presents a comparison of different configurations of a wireless sensor system for capturing human motion. The systems consist of sensor elements which wirelessly transfers motion data to a receiver element. The ...
Demo Paper: Advanced Partial Run-time Reconfiguration on Spartan-6 FPGAs 
Koch, Dirk; Beckhoff, Christian; Tørresen, Jim (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2010)
In this paper, we demonstrate systems based on Spartan-6 series FPGAs that provide full support for active partial run-time reconfiguration. We will summarize design factors for successfully applying run-time reconfiguration, ...
Robotics and Intelligent Systems at University of Oslo 
Tørresen, Jim; Glette, Kyrre Harald; Jensenius, Alexander Refsum; Furuholmen, Marcus (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2009)
The Robotics and Intelligent Systems group conducts research in the interdisciplinary field of robotics, machine learning, reconfigurable hardware and sensing human actions. The group is affiliated to the Department of ...
 
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Date Issued2010 - 2020 (44)2009 - 2009 (1)Document TypeBokkapittel (30)Tidsskriftartikkel (15)Author
Tørresen, Jim (45)
Jensenius, Alexander Refsum (13)Nymoen, Kristian (10)Glette, Kyrre (8)Martin, Charles Patrick (8)... View MorePeer ReviewedPeer reviewed (44)
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