51 citations · 260 across the 30 of their papers we have counts for
31 papers
Offline Skill Generalization via Task and Motion Planning
Shin Watanabe, Geir Horn, Jim Tørresen +1
This paper presents a novel approach to generalizing robot manipulation skills by combining a sampling-based task-and-motion planner with an offline reinforcement learning algorith…
Rafting Towards Consensus: Formation Control of Distributed Dynamical Systems
Abbas Tariverdi, Jim Torresen
In this paper, we introduce a novel adaptation of the Raft consensus algorithm for achieving emergent formation control in multi-agent systems with a single integrator dynamics. Th…
Robotics in Elderly Healthcare: A Review of 20 Recent Research Projects
Weria Khaksar, Diana Saplacan, Lee Andrew Bygrave +1
Studies show dramatic increase in elderly population of Western Europe over the next few decades, which will put pressure on healthcare systems. Measures must be taken to meet thes…
Latent Space Unsupervised Semantic Segmentation
Knut J. Strømmen, Jim Tørresen, Ulysse Côté-Allard
The development of compact and energy-efficient wearable sensors has led to an increase in the availability of biosignals. To analyze these continuously recorded, and often multidi…
Adherence Forecasting for Guided Internet-Delivered Cognitive Behavioral Therapy: A Minimally Data-Sensitive Approach
Ulysse Côté-Allard, Minh H. Pham, Alexandra K. Schultz +2
Internet-delivered psychological treatments (IDPT) are seen as an effective and scalable pathway to improving the accessibility of mental healthcare. Within this context, treatment…
Reinforcement Learning-based Switching Controller for a Milliscale Robot in a Constrained Environment
Abbas Tariverdi, Ulysse Côté-Allard, Kim Mathiassen +4
This work presents a reinforcement learning-based switching control mechanism to autonomously move a ferromagnetic object (representing a milliscale robot) around obstacles within…
A Lower Bound on Latency Spikes for Capacity-Seeking Network Traffic
Bjørn Ivar Teigen, Neil Davies, Kai Olav Ellefsen +3
Most Internet traffic is carried by capacity-seeking protocols such as TCP and QUIC. Capacity-seeking protocols probe to find the maximum available throughput from sender to receiv…
Long-Short Ensemble Network for Bipolar Manic-Euthymic State Recognition Based on Wrist-worn Sensors
Ulysse Côté-Allard, Petter Jakobsen, Andrea Stautland +4
Manic episodes of bipolar disorder can lead to uncritical behaviour and delusional psychosis, often with destructive consequences for those affected and their surroundings. Early d…
A Model of WiFi Performance With Bounded Latency
Bjørn Ivar Teigen, Neil Davies, Kai Olav Ellefsen +2
In September 2020, the Broadband Forum published a new industry standard for measuring network quality. The standard centers on the notion of quality attenuation. Quality attenuati…
Composing an Ensemble Standstill Work for Myo and Bela
Charles Patrick Martin, Alexander Refsum Jensenius, Jim Torresen
This paper describes the process of developing a standstill performance work using the Myo gesture control armband and the Bela embedded computing platform. The combination of Myo…
Towards Movement Generation with Audio Features
Benedikte Wallace, Charles P. Martin, Jim Torresen +1
Sound and movement are closely coupled, particularly in dance. Certain audio features have been found to affect the way we move to music. Is this relationship between sound and mov…
Differences of Human Perceptions of a Robot Moving using Linear or Slow in, Slow out Velocity Profiles When Performing a Cleaning Task
Trenton Schulz, Patrick Holthaus, Farshid Amirabdollahian +3
We investigated how a robot moving with different velocity profiles affects a person's perception of it when working together on a task. The two profiles are the common linear prof…
Environmental Adaptation of Robot Morphology and Control through Real-world Evolution
Tønnes F. Nygaard, Charles P. Martin, David Howard +2
Robots operating in the real world will experience a range of different environments and tasks. It is essential for the robot to have the ability to adapt to its surroundings to wo…
Self-Adapting Goals Allow Transfer of Predictive Models to New Tasks
Kai Olav Ellefsen, Jim Torresen
A long-standing challenge in Reinforcement Learning is enabling agents to learn a model of their environment which can be transferred to solve other problems in a world with the sa…
An Interactive Musical Prediction System with Mixture Density Recurrent Neural Networks
Charles P Martin, Jim Torresen
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…
Two-Stage Transfer Learning for Heterogeneous Robot Detection and 3D Joint Position Estimation in a 2D Camera Image using CNN
Justinas Miseikis, Inka Brijacak, Saeed Yahyanejad +3
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 n…
Evolving Robots on Easy Mode: Towards a Variable Complexity Controller for Quadrupeds
Tønnes Frostad Nygaard, Charles Patrick Martin, Jim Torresen +1
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 -…
Data Driven Analysis of Tiny Touchscreen Performance with MicroJam
Charles P Martin, Jim Torresen
The widespread adoption of mobile devices, such as smartphones and tablets, has made touchscreens a common interface for musical performance. New mobile musical instruments have be…
Guiding Neuroevolution with Structural Objectives
Kai Olav Ellefsen, Joost Huizinga, Jim Torresen
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…
How do Mixture Density RNNs Predict the Future?
Kai Olav Ellefsen, Charles Patrick Martin, Jim Torresen
Gaining a better understanding of how and what machine learning systems learn is important to increase confidence in their decisions and catalyze further research. In this paper, w…
Animation Techniques in Human-Robot Interaction User Studies: a Systematic Literature Review
Trenton Schulz, Jim Torresen, Jo Herstad
There are many different ways a robot can move in Human-Robot Interaction. One way is to use techniques from film animation to instruct the robot to move. This article is a systema…
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…