Tønnes Nygaard

• Nygaard, Tønnes; Tiderko, Alexander; Schneider, Frank E.; Bounker, Paul; Glówka, Jakub & Nielsen, Niels Hygum [Show all 8 contributors for this article] (2025). Interoperability for Semi-Autonomous Unmanned Ground Vehicles, 2025 International Conference on Military Communication and Information Systems (ICMCIS). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331537869. doi: 10.1109/icmcis64378.2025.11047908. Full text in Research Archive Show summary

  This paper describes the NATO STO IST-179-RTG group's efforts to improve interoperability of semiautonomous unmanned ground vehicles. Through experiments and demonstrations at major events like the European Robotics Hackathon 2021 and the European Land-Robot Trial 2022, a practical application of interoperability standards was investigated in different real-world scenarios, demonstrating both current capabilities and potential areas of improvement. This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-209-RSY - the ICMCIS, held in Oeiras, Portugal, 13–14 May 2025

• Lofstad-Lie, Victoria; Simonsen, Aleksander; Nygaard, Tønnes & Marstein, Erik Stensrud (2025). Data Quality Analyses for Automatic Aerial Thermography Inspection of PV Power Plants. IEEE Journal of Photovoltaics. ISSN 2156-3381. 15(5), p. 722–731. doi: 10.1109/JPHOTOV.2025.3587297. Full text in Research Archive
• Tveter, Mats; Tveitstøl, Thomas; Nygaard, Tønnes; Teseyra, Ana Silvina Pérez; Kulashekhar, Shrikanth & Bruña, Ricardo [Show all 9 contributors for this article] (2024). EEG electrodes and where to find them: automated localization from 3D scans. Journal of Neural Engineering. ISSN 1741-2560. 21(5). doi: 10.1088/1741-2552/ad7c7e. Full text in Research Archive Show summary

  Objective The accurate localization of electroencephalography (EEG) electrode positions is crucial for accurate source localization. Recent advancements have proposed alternatives to labor-intensive, manual methods for spatial localization of the electrodes, employing technologies such as 3D scanning and laser scanning. These novel approaches often integrate magnetic resonance imaging (MRI) as part of the pipeline in localizing the electrodes. The limited global availability of MRI data restricts its use as a standard modality in several clinical scenarios. This limitation restricts the use of these advanced methods. Approach In this paper, we present a novel, versatile approach that utilizes 3D scans to localize EEG electrode positions with high accuracy. Importantly, while our method can be integrated with MRI data if available, it is specifically designed to be highly effective even in the absence of MRI, thus expanding the potential for advanced EEG analysis in various resource-limited settings. Our solution implements a two-tiered approach involving landmark/fiducials localization and electrode localization, creating an end-to-end framework. Main results The efficacy and robustness of our approach have been validated on an extensive dataset containing over 400 3D scans from 278 subjects. The framework identifies pre-auricular points and achieves correct electrode positioning accuracy in the range of 85.7% to 91.0%. Additionally, our framework includes a validation tool that permits manual adjustments and visual validation if required. Significance This study represents, to the best of the authors’ knowledge, the first validation of such a method on a substantial dataset, thus ensuring the robustness and generalizability of our innovative approach. Our findings focus on developing a solution that facilitates source localization, without the need for MRI, contributing to the critical discussion on balancing cost effectiveness with methodological accuracy to promote wider adoption in both research and clinical settings.

• Nilsen, Mathias Kvamme; Nygaard, Tønnes & Ellefsen, Kai Olav (2023). Reward tampering and evolutionary computation: a study of concrete AI-safety problems using evolutionary algorithms. Genetic Programming and Evolvable Machines. ISSN 1389-2576. 24(2). doi: 10.1007/s10710-023-09456-0. Full text in Research Archive Show summary

  Abstract Reward tampering is a problem that will impact the trustworthiness of the powerful AI systems of the future. Reward Tampering describes the problem where AI agents bypass their intended objective, enabling unintended and potentially harmful behaviours. This paper investigates whether the creative potential of evolutionary algorithms could help ensure trustworthy solutions when facing this problem. The reason why evolutionary algorithms may help combat reward tampering is that they are able to find a diverse collection of different solutions to a problem within a single run, aiding the search for desirable solutions. Four different evolutionary algorithms were deployed in tasks illustrating the problem of reward tampering. The algorithms were designed with varying degrees of human expertise, measuring how human guidance influences the ability to discover trustworthy solutions. The results indicate that the algorithms’ ability to find and preserve trustworthy solutions is very dependent on preserving diversity during the search. Algorithms searching for behavioural diversity showed to be the most effective against reward tampering. Human expertise also showed to improve the certainty and quality of safe solutions, but even with only a minimal degree of human expertise, domain-independent diversity management was found to discover safe solutions.

• Norstein, Emma Stensby; Veenstra, Frank; Ellefsen, Kai Olav; Nygaard, Tønnes & Glette, Kyrre (2023). Effects of compliant and structural parts in evolved modular robots. In Iizuki, Hiroyuki; Suzuki, Keisuke; Uno, Ryoko; Damiano, Luisa; Spychala, Nadine; Aguilera, Miguel; Izquierdo, Eduardo; Suzuki, Reiji & Baltieri, Manuel (Ed.), ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. MIT Press. doi: 10.1162/isal_a_00689. Full text in Research Archive Show summary

  A striking difference between animals and traditional robots is that the latter usually have rigid and non-flexible bodies. Animals, on the other hand, exhibit highly adapted traits, such as elastic tendons. The tendons work as springs, storing and releasing kinetic energy during an animal’s gait cycle. Springs have been used in some hand designed robots for similar benefits. However, little research has been done on springs in robots with evolving morphology. We examine the use of compliant and structural modules in modular robots, using a standard evolutionary algorithm. We also look at connections between spring stiffness and robot size using the quality diversity algorithm MAP-Elites. We found that the modular robots evolved to use elastic actuators, and that structural modules enabled morphologies that use less actuators, but still achieve the same walking speed as the robots with actuators in every module. We also observe some indications that larger robots may require lower elasticity.

• Norstein, Emma Stensby; Ellefsen, Kai Olav; Veenstra, Frank; Nygaard, Tønnes & Glette, Kyrre (2023). Evolution of linkages for prototyping of linkage based robots, Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665487689. p. 1283–1290. doi: 10.1109/SSCI51031.2022.10022197. Full text in Research Archive Show summary

  Prototyping robotic systems is a time consuming process. Computer aided design, however, might speed up the process significantly. Quality-diversity evolutionary approaches optimise for novelty as well as performance, and can be used to generate a repertoire of diverse designs. This design repertoire could be used as a tool to guide a designer and kick-start the rapid prototyping process. This paper explores this idea in the context of mechanical linkage based robots. These robots can be a good test-bed for rapid prototyping, as they can be modified quickly for swift iterations in design. We compare three evolutionary algorithms for optimising 2D mechanical linkages: 1) a standard evolutionary algorithm, 2) the multi-objective algorithm NSGA-II, and 3) the quality-diversity algorithm MAP-Elites. Some of the found linkages are then realized on a physical hexapod robot through a prototyping process, and tested on two different floors. We find that all the tested approaches, except the standard evolutionary algorithm, are capable of finding mechanical linkages that creates a path similar to a specified desired path. However, the quality-diversity approaches that had the length of the linkage as a behaviour descriptor were the most useful when prototyping. This was due to the quality-diversity approaches having a larger variety of similar designs to choose from, and because the search could be constrained by the behaviour descriptors to make linkages that were viable for construction on our hexapod platform.

• Nygaard, Tønnes Frostad & Glette, Kyrre (2022). Benefits and Challenges of Morphological Adaptation in Real-world Robots. IOP Conference Series: Materials Science and Engineering. ISSN 1757-8981. 1261. doi: 10.1088/1757-899X/1261/1/012017. Full text in Research Archive Show summary

  Abstract For many years, the main target of robotics research has been how to improve control and behavior to allow robots to solve more challenging tasks. Recently, the concept of embodied intelligence has shifted this focus from pure control to a more holistic approach. The mind, body, environment, and the interactions between all these are all highly important for the performance of a robot system. This has previously been investigated in virtual robots in simulation or very simple physical robots in the lab, but the benefits for more advanced and capable real-world robots are still to be determined. We present a case study with several examples of real-world adaptation of morphology, and discuss the benefits and challenges as this direction becomes more important in the field of robotics. Taking an embodied approach promises more adaptive and robust robots, but there are many challenges that need to be addressed before wide-spread adoption in the robotics community.

• Ahmadi, Ahmadreza; Nygaard, Tønnes; Kottege, Navinda; Howard, David & Hudson, Nicolas (2021). Semi-Supervised Gated Recurrent Neural Networks for Robotic Terrain Classification. IEEE Robotics and Automation Letters. ISSN 2377-3766. 6(2), p. 1848–1855. doi: 10.1109/LRA.2021.3060437. Full text in Research Archive
• Nordmoen, Jørgen; Nygaard, Tønnes Frostad; Samuelsen, Eivind & Glette, Kyrre (2021). On Restricting Real-Valued Genotypes in Evolutionary Algorithms. In Castillo, Pedro A. & Laredo, Juan Luiz Jiménez (Ed.), Applications of Evolutionary Computation. Springer. ISSN 9783030726997. p. 3–16. doi: 10.1007/978-3-030-72699-7_1. Full text in Research Archive Show summary

  Real-valued genotypes together with the variation operators, mutation and crossover, constitute some of the fundamental building blocks of Evolutionary Algorithms. Real-valued genotypes are utilized in a broad range of contexts, from weights in Artificial Neural Networks to parameters in robot control systems. Shared between most uses of real-valued genomes is the need for limiting the range of individual parameters to allowable bounds. In this paper we will illustrate the challenge of limiting the parameters of real-valued genomes and analyse the most promising method to properly limit these values. We utilize both empirical as well as benchmark examples to demonstrate the utility of the proposed method and through a literature review show how the insight of this paper could impact other research within the field. The proposed method requires minimal intervention from Evolutionary Algorithm practitioners and behaves well under repeated application of variation operators, leading to better theoretical properties as well as significant differences in well-known benchmarks.

• Nygaard, Tønnes; Martin, Charles Patrick; Tørresen, Jim; Glette, Kyrre & Howard, David (2021). Real-world embodied AI through a morphologically adaptive quadruped robot. Nature Machine Intelligence. doi: 10.1038/s42256-021-00320-3. Full text in Research Archive Show summary

  Robots are traditionally bound by a fixed morphology during their operational lifetime, which is limited to adapting only their control strategies. Here we present the first quadrupedal robot that can morphologically adapt to different environmental conditions in outdoor, unstructured environments. Our solution is rooted in embodied AI and comprises two components: (1) a robot that permits in situ morphological adaptation and (2) an adaptation algorithm that transitions between the most energy-efficient morphologies on the basis of the currently sensed terrain. We first build a model that describes how the robot morphology affects performance on selected terrains. We then test continuous adaptation on realistic outdoor terrain while allowing the robot to constantly update its model. We show that the robot exploits its training to effectively transition between different morphological configurations, exhibiting substantial performance improvements over a non-adaptive approach. The demonstrated benefits of real-world morphological adaptation demonstrate the potential for a new embodied way of incorporating adaptation into future robotic designs.

• Nygaard, Tønnes; Martin, Charles Patrick; Howard, David; Tørresen, Jim & Glette, Kyrre (2021). Environmental Adaptation of Robot Morphology and Control Through Real-world Evolution. Evolutionary Computation. ISSN 1063-6560. doi: 10.1162/evco_a_00291. Full text in Research Archive Show summary

  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 work efficiently in changing conditions. Evolutionary robotics aims to solve this by optimizing both the control and body (morphology) of a robot, allowing adaptation to internal, as well as external factors. Most work in this field has been done in physics simulators, which are relatively simple and not able to replicate the richness of interactions found in the real world. Solutions that rely on the complex interplay between control, body, and environment are therefore rarely found. In this paper, we rely solely on real-world evaluations and apply evolutionary search to yield combinations of morphology and control for our mechanically self-reconfiguring quadruped robot. We evolve solutions on two distinct physical surfaces and analyze the results in terms of both control and morphology. We then transition to two previously unseen surfaces to demonstrate the generality of our method. We find that the evolutionary search finds high-performing and diverse morphology-controller configurations by adapting both control and body to the different properties of the physical environments. We additionally find that morphology and control vary with statistical significance between the environments. Moreover, we observe that our method allows for morphology and control parameters to transfer to previously-unseen terrains, demonstrating the generality of our approach.

• Nygaard, Tønnes; Howard, David & Glette, Kyrre (2020). Real world morphological evolution is feasible. In Coello, Carlos A. Coello (Eds.), GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM). ISSN 9781450371278. p. 1392–1394. doi: 10.1145/3377929.3398095. Full text in Research Archive Show summary

  Evolutionary algorithms offer great promise for the automatic design of robot bodies, tailoring them to specific environments or tasks. Most research is done on simplified models or virtual robots in physics simulators, which do not capture the natural noise and richness of the real world. Very few of these virtual robots are built as physical robots, and the few that are will rarely be further improved in the actual environment they operate in, limiting the effectiveness of the automatic design process. We utilize our shape-shifting quadruped robot, which allows us to optimize the design in its real-world environment. The robot is able to change the length of its legs during operation, and is robust enough for complex experiments and tasks. We have co-evolved control and morphology in several different scenarios, and have seen that the algorithm is able to exploit the dynamic morphology solely through real-world experiments.

• Forberg, Henrik Storm; Nygaard, Tønnes & Høvin, Mats Erling (2020). Generative Truss Optimization for Support-Free Fused Filament Fabrication. In Arabnia, Hamid R.; Deligiannidis, Leonidas; Tinetti, Fernando G. & Tran, Quoc-Nam (Ed.), Proceedings of 2020 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE Computer Society Digital Library. ISSN 9781728176246. p. 149–1497. Full text in Research Archive
• Martin, Charles Patrick; Glette, Kyrre; Nygaard, Tønnes & Tørresen, Jim (2020). Understanding Musical Predictions With an Embodied Interface for Musical Machine Learning. Frontiers in Artificial Intelligence. 3(6). doi: 10.3389/frai.2020.00006. Full text in Research Archive Show summary

  Machine-learning models of music often exist outside the worlds of musical performance practice and abstracted from the physical gestures of musicians. In this work, we consider how a recurrent neural network (RNN) model of simple music gestures may be integrated into a physical instrument so that predictions are sonically and physically entwined with the performer's actions. We introduce EMPI, an embodied musical prediction interface that simplifies musical interaction and prediction to just one dimension of continuous input and output. The predictive model is a mixture density RNN trained to estimate the performer's next physical input action and the time at which this will occur. Predictions are represented sonically through synthesized audio, and physically with a motorized output indicator. We use EMPI to investigate how performers understand and exploit different predictive models to make music through a controlled study of performances with different models and levels of physical feedback. We show that while performers often favor a model trained on human-sourced data, they find different musical affordances in models trained on synthetic, and even random, data. Physical representation of predictions seemed to affect the length of performances. This work contributes new understandings of how musicians use generative ML models in real-time performance backed up by experimental evidence. We argue that a constrained musical interface can expose the affordances of embodied predictive interactions.

• Nygaard, Tønnes Frostad; Nordmoen, Jørgen Halvorsen; Ellefsen, Kai Olav; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Experiences from Real-World Evolution with DyRET: Dynamic Robot for Embodied Testing, Nordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019. Springer. ISSN 9783030356644. p. 58–68. doi: 10.1007/978-3-030-35664-4_6. Full text in Research Archive
• Nygaard, Tønnes Frostad; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing. IEEE International Conference on Robotics and Automation (ICRA). ISSN 1050-4729. 2019-May, p. 9446–9452. doi: 10.1109/ICRA.2019.8793663. Full text in Research Archive Show summary

  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. Previous work on dynamic robot morphology has focused on simulation, combining simple modules, or switching between locomotion modes. Here, we present an alternative approach: a self-reconfigurable morphology that allows a single four-legged robot to actively adapt the length of its legs to different environments. We report the design of our robot, as well as the results of a study that verifies the performance impact of self-reconfiguration. This study compares three different control and morphology pairs under different levels of servo supply voltage in the lab. We also performed preliminary tests in different uncontrolled outdoor environments to see if changes to the external environment supports our findings in the lab. Our results show better performance with an adaptable body, lending evidence to the value of self-reconfiguration for quadruped robots.

• Nygaard, Tønnes Frostad; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Evolving Robots on Easy Mode: Towards a Variable Complexity Controller for Quadrupeds. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11454 LNCS, p. 616–632. doi: 10.1007/978-3-030-16692-2_41. Full text in Research Archive Show summary

  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 for physical robots. For some tasks, a more general gait, with lower optimization costs, could be satisfactory. In this paper, we introduce a new type of gait controller where complexity can be set by a single parameter, using a dynamic genotype-phenotype mapping. Low controller complexity leads to conservative gaits, while higher complexity allows more sophistication and high performance for demanding tasks, at the cost of optimization effort. We investigate the new controller on a virtual robot in simulations and do preliminary testing on a real-world robot. We show that having variable complexity allows us to adapt to different optimization budgets. With a high evaluation budget in simulation, a complex controller performs best. Moreover, real-world evolution with a limited evaluation budget indicates that a lower gait complexity is preferable for a relatively simple environment.

• Nordmoen, Jørgen Halvorsen; Nygaard, Tønnes Frostad; Ellefsen, Kai Olav & Glette, Kyrre (2019). Evolved embodied phase coordination enables robust quadruped robot locomotion. In López-Ibáñez, Manuel (Eds.), GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM). ISSN 9781450361118. p. 133–141. doi: 10.1145/3321707.3321762. Full text in Research Archive Show summary

  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 automatically design such control systems, however, if the disparity between simulation and the real world becomes too large, the optimization process may result in dysfunctional real-world behaviors. In this paper, we address this challenge by considering embodied phase coordination in the evolutionary optimization of a quadruped robot controller based on central pattern generators. With this method, leg phases, and indirectly also inter-leg coordination, are influenced by sensor feedback. By comparing two very similar control systems we gain insight into how the sensory feedback approach affects the evolved parameters of the control system, and how the performances differ in simulation, in transferal to the real world, and to different real-world environments. We show that evolution enables the design of a control system with embodied phase coordination which is more complex than previously seen approaches, and that this system is capable of controlling a real-world multi-jointed quadruped robot. The approach reduces the performance discrepancy between simulation and the real world, and displays robustness towards new environments.

• Nygaard, Tønnes Frostad; Martin, Charles Patrick; Samuelsen, Eivind; Tørresen, Jim & Glette, Kyrre (2018). Real-world evolution adapts robot morphology and control to hardware limitations. In aguirre, hernan (Eds.), GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM). ISSN 9781450356183. p. 125–132. doi: 10.1145/3205455.3205567. Full text in Research Archive Show summary

  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 these issues by automatically optimizing a robot for a specific environment. Most of the research in this field, however, uses simplified representations of the robotic system in software simulations. The large gap between performance in simulation and the real world makes it challenging to transfer the resulting robots to the real world. In this paper, we apply real world multi-objective evolutionary optimization to optimize both control and morphology of a four-legged mammal-inspired robot. We change the supply voltage of the system, reducing the available torque and speed of all joints, and study how this affects both the fitness, as well as the morphology and control of the solutions. In addition to demonstrating that this real-world evolutionary scheme for morphology and control is indeed feasible with relatively few evaluations, we show that evolution under the different hardware limitations results in comparable performance for low and moderate speeds, and that the search achieves this by adapting both the control and the morphology of the robot.

• Nygaard, Tønnes Frostad; Samuelsen, Eivind & Glette, Kyrre (2017). Overcoming initial convergence in multi-objective evolution of robot control and morphology using a two-phase approach. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 10199 LNCS(Part I), p. 825–836. doi: 10.1007/978-3-319-55849-3_53. Full text in Research Archive Show summary

  Co-evolution of robot morphologies and control systems is a new and interesting approach for robotic design. However, the increased size and ruggedness of the search space becomes a challenge, often leading to early convergence with sub-optimal morphology-controller combinations. Further, mutations in the robot morphologies tend to cause large perturbations in the search, effectively changing the environment, from the controller’s perspective. In this paper, we present a two-stage approach to tackle the early convergence in morphology-controller co-evolution. In the first phase, we allow free evolution of morphologies and controllers simultaneously, while in the second phase we re-evolve the controllers while locking the morphology. The feasibility of the approach is demonstrated in physics simulations, and later verified on three different real-world instances of the robot morphologies. The results demonstrate that by introducing the two-phase approach, the search produces solutions which outperform the single co-evolutionary run by over 10%. © 2017 Springer Verlag

• Nygaard, Tønnes Frostad; Tørresen, Jim & Glette, Kyrre (2016). Multi-objective Evolution of Fast and Stable Gaits on a Physical Quadruped Robotic Platform. In Jin, Yaochu & Kollias, Stefanos (Ed.), Proc. of 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781509042401. doi: 10.1109/SSCI.2016.7850167. Full text in Research Archive

View all works in NVA

• Nygaard, Tønnes Frostad & Bushwick, Sophie (2023). Mighty Morpher. [Journal]. Scientific American. Full text in Research Archive
• Nygaard, Tønnes (2023). Selvgående drapsmaskiner - Forsvarets nye leketøy vekker oppsikt. [Journal]. Vi Menn. Full text in Research Archive
• Nygaard, Tønnes (2023). Roboten Freke – Hvordan kan kunstig intelligens bidra til å øke Norges sikkerhet og beredskap? Full text in Research Archive
• Nygaard, Tønnes Frostad & Mentzoni, Eilert André (2022). Robothunder og selvkjørende biler tar Forsvaret inn i fremtiden. [Internet]. Forsvaret.no. Full text in Research Archive
• Nygaard, Tønnes Frostad & Bjørk, Hanne Marit (2022). Norsk, sivil teknologi fornyer forsvaret: - Vi står overfor en revolusjon. [Internet]. kode24.no. Full text in Research Archive
• Nygaard, Tønnes Frostad (2022). Robothunden – menneskets nye bestevenn? Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2022). This Cheetah Robot Taught Itself How to Sprint in a Weird Way. [Internet]. Wired.com. Full text in Research Archive
• Nygaard, Tønnes Frostad & Torgersen, Eivind (2021). Denne roboten endrer lengden på beina når den går fra gress til betong. [Internet]. Forskning.no. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2021). Watch a Shape-Shifting Robot Prowl the Big, Bad World. [Internet]. Wired.com. Full text in Research Archive
• Nygaard, Tønnes Frostad; Leirvik, Jan børge; Grov, Benedikte & Marvik, Jo Arne (2021). Robothund kan bli vaktmeisterens beste venn. [Internet]. NRK. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2021). How Do You Make a Robot Walk on Mars? It’s a Steep Challenge. [Internet]. Wired.com. Full text in Research Archive
• Nygaard, Tønnes Frostad & Spry, Jeff (2021). Meet Spacebok, the radical new rover built to jump around the moon and mars. [Internet]. syfy.com. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2021). See little robots get swole in this virtual ‘gym’. [Internet]. Wired.com. Full text in Research Archive
• Nygaard, Tønnes Frostad (2021). Morphology Adaptation in Real-world Robots. Full text in Research Archive
• Elverhøy, Hilmar; Bøe, Steinar; Søyseth, Vegard & Nygaard, Tønnes (2021). Ankle Joints Are Beneficial When Optimizing Supported Real-world Bipedal Robot Gaits. arXiv. doi: 10.48550/arXiv.2105.10764. Full text in Research Archive
• Ellefsen, Kai Olav; Nygaard, Tønnes Frostad & Kjørstad, Elise (2020). Her er den første roboten som er laget av levende celler. [Internet]. forskning.no. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2020). Meet Xenobot, an Eerie New Kind of Programmable Organism. [Internet]. Wired.com. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2019). Inside Facebook's New Robotics Lab, Where AI and Machines Friend One Another. [Journal]. Wired. Full text in Research Archive
• Nygaard, Tønnes Frostad; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing. Full text in Research Archive
• Nygaard, Tønnes Frostad; Nordmoen, Jørgen Halvorsen; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Lessons Learned from Real-World Experiments with DyRET: the Dynamic Robot for Embodied Testing. Full text in Research Archive
• Nygaard, Tønnes Frostad & Glette, Kyrre (2019). Her er universitetets mest avanserte, selvlærende robot. [Journal]. Apollon. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2019). The Clever Clumsiness of a Robot Teaching Itself to Walk. [Journal]. Wired Science. Full text in Research Archive
• Glette, Kyrre; Nygaard, Tønnes Frostad & Vogt, Yngve (2019). Her er universitetets nest selvlærende robot. [Journal]. Teknisk ukeblad. Full text in Research Archive
• Nordmoen, Jørgen Halvorsen; Nygaard, Tønnes Frostad; Ellefsen, Kai Olav & Glette, Kyrre (2019). Evolved embodied phase coordination enables robust quadruped robot locomotion. Full text in Research Archive
• Nygaard, Tønnes Frostad; Nordmoen, Jørgen Halvorsen; Ellefsen, Kai Olav; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2019). Experiences from Real-World Evolution with DyRET: Dynamic Robot for Embodied Testing. Full text in Research Archive
• Nygaard, Tønnes Frostad & Dormehl, Luke (2018). This robot taught itself how to walk and it’s as clumsy as a newborn deer. [Journal]. Digital Trends. Full text in Research Archive
• Nygaard, Tønnes Frostad & Gonzales, Robbie (2018). How a Flock of Drones Developed Collective Intelligence. [Journal]. Wired Science. Full text in Research Archive
• Nygaard, Tønnes Frostad & Papadopoulos, Loukia (2018). New Evolving Robot Teaches Itself to Walk Through Trial and Error. [Journal]. Interesting Engineering. Full text in Research Archive
• Nygaard, Tønnes Frostad & Simon, Matt (2018). The shape-shifting robot that evolves by falling down. [Journal]. Wired Science. Full text in Research Archive
• Moen, Hans Jonas Fossum; Glette, Kyrre; Nygaard, Tønnes Frostad & Johnsrud, Mette (2018). Fem felt der vi får en førerløs fremtid. [Internet]. Titan.uio.no. Full text in Research Archive
• Martin, Charles Patrick; Glette, Kyrre; Nygaard, Tønnes Frostad & Tørresen, Jim (2018). Self-Awareness in a Cyber-Physical Predictive Musical Interface. Full text in Research Archive Show summary

  We introduce a new self-contained and self-aware interface for musical expression where a recurrent neural network (RNN) is integrated into a physical instrument design. The system includes levers for physical input and output, a speaker system, and an integrated single-board computer. The RNN serves as an internal model of the user’s physical input, and predictions can replace or complement direct sonic and physical control by the user. We explore this device in terms of different interaction configurations and learned models according to frameworks of self-aware cyber-physical systems.

• Nygaard, Tønnes Frostad; Martin, Charles Patrick; Tørresen, Jim & Glette, Kyrre (2018). Exploring Mechanically Self-Reconfiguring Robots for Autonomous Design. Full text in Research Archive Show summary

  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, and does this only in simulation. We have developed a four-legged mammal-inspired robot that features a self-reconfiguring morphology. In this paper, we discuss the possibilities opened up by being able to efficiently do experiments on a changing morphology in the real world. We discuss present challenges for such a platform and potential experimental designs that could unlock new discoveries. Finally, we place our robot in its context within general developments in the field of evolutionary robotics, and consider what advances the future might hold.

• Nygaard, Tønnes Frostad; Søyseth, Vegard Dønnem; Nordmoen, Jørgen Halvorsen & Glette, Kyrre (2018). Stand with the DyRET robot. Full text in Research Archive
• Nygaard, Tønnes Frostad (2018). Real-World Evolution Adapts Robot Morphology and Control to Hardware Limitations. Full text in Research Archive
• Nygaard, Tønnes Frostad (2018). DyRET: Dynamic Robot for Embodied Testing. Full text in Research Archive
• Søyseth, Vegard Dønnem; Nygaard, Tønnes Frostad; Martin, Charles Patrick; Uddin, Md Zia & Ellefsen, Kai Olav (2018). ROBIN-Stand ved Cutting Edge 2018. Full text in Research Archive
• Nygaard, Tønnes Frostad & Eikenes, Åsmund H. (2017). Robotane må tilpasse seg oss menneske. [Journal]. Framtida.no. Full text in Research Archive
• Martin, Charles Patrick; Sanchez, Victor Evaristo Gonzalez; Kelkar, Tejaswinee; Zelechowska, Agata; Berggren, Stig Johan & Hopgood, Christina [Show all 14 contributors for this article] (2017). Ensemble Metatone - Improvised Touchscreen Performance. Full text in Research Archive
• Nygaard, Tønnes Frostad (2017). Presentation on Robotics: Today and the future. Full text in Research Archive
• Nygaard, Tønnes Frostad & Haugnes, Gunhild (2016). Nå kommer robotene som lærer som et menneske. [Journal]. Titan. Full text in Research Archive
• Glette, Kyrre Harald; Nygaard, Tønnes Frostad; Grutle, Øyvind Kallevik; Miseikis, Justinas & Drews, Haakon (2015). Robotikk og intelligente systemer (stand). Full text in Research Archive
• Glette, Kyrre Harald; Høvin, Mats Erling; Samuelsen, Eivind; Nygaard, Tønnes Frostad & Temperton, James (2014). 3D printed evolving robots destined for disaster zones. [Journal]. wired.co.uk. Full text in Research Archive
• Glette, Kyrre Harald; Samuelsen, Eivind & Nygaard, Tønnes Frostad (2014). Evolusjonær robotikk. Full text in Research Archive
• Vogt, Yngve; Samuelsen, Eivind; Glette, Kyrre Harald; Nygaard, Tønnes Frostad & Høvin, Mats Erling (2014). Skriver ut selvlærende roboter. [Journal]. Apollon : Forskningsmagasin for Universitetet i Oslo. Full text in Research Archive
• Bakstad, Lorns Harald; Baksaas, Magnus; Mygland, Katrine; Eikanger, Brage Gerdssønn; Gusland, Daniel & Hauge, Mariann [Show all 23 contributors for this article] (2025). LandX21 – teknologi i framtidas stridsfelt. Forsvarets forskningsinstitutt . Full text in Research Archive Show summary

  Etter suksessen med LandX i 2020 besluttet FFI å holde LandX som et årlig eksperiment. To uker hver høst skal forskere, brukere og industri samles på Rena for å eksperimentere med teknologi og nye løsninger for Forsvaret. Eksperimentukene avsluttes med en demonstrasjon for inviterte fra hele sektoren. Målet med demonstrasjonen er å formidle forskning til relevante brukere i Forsvaret og demonstrere hvordan ny teknologi kan bidra til å endre framtidas stridsfelt i landdomenet. I 2021 var temaet for LandX situasjonsforståelse, og forskningsprosjekter fra fem forskningsprogrammer ved FFI deltok. Eksperimenteringen dekket alt fra ubemannede og autonome systemer på bakken og i lufta til sensorfusjon, målfølging og robust og sikker kommunikasjon. I tillegg markerte LandX21 åpningen av FFIs nye innovasjonsarena, ICE worx Rena. I denne rapporten oppsummerer vi innholdet og resultatene fra eksperimentene helt overordnet og peker på relevante rapporter som kan utdype teknologien ytterligere. LandX21 var en suksess. Forskningsprogrammene rapporterte i ettertid at de hadde kommet lenger og lært mer enn de hadde gjort om de ikke hadde testet i felt. Tilbakemeldingene fra tilskuerne på demonstrasjonsdagen var at forskningsarbeidet hadde høy relevans, og at det ble formidlet på en god måte. LandX skal arrangeres igjen i 2022. Da skal vi utvide omfanget, og målsetningen er å samarbeide tettere med brukere for å få enda bedre kobling mellom forskningen og operativ bruk.

• Nygaard, Tønnes; Glette, Kyrre; Tørresen, Jim & Martin, Charles Patrick (2020). Legging It: An Evolutionary Approach to Morphological Adaptation for a Real-World Quadruped Robot. Universitetet i Oslo. Full text in Research Archive Show summary

  Robots are used in increasingly complex environments and need to be able to adapt to changes and unexpected events. This has traditionally been solved by changing the control of a robot, but having an adjustable body can unlock new and powerful adaptive capabilities. An adaptive morphology allows tuning of the physical structure of the robot to different, often conflicting, dynamic requirements, including speed, stability, and efficiency. It can also unlock new functionalities that might not be possible with static morphologies, including variable gearing and multiple locomotion modalities. Even with the potential benefits of morphological adaptation, the methods and technology are still not at a point where there is wide-spread use of adaptive morphologies in physical robots. The main goal of the thesis is to develop methods and technology to enable adaptation of the physical body of a robot to new real-world environments. An evolutionary approach is taken, and to what degree evolutionary algorithms are able to exploit the dynamic morphology of a legged robot is investigated. The feasibility of continuous adaptation of morphology in realistic outdoor environments is also explored. A quadruped mammal-inspired robot with the ability to continuously adjust the length of its legs during operation has been designed and implemented as part of the work outlined in the thesis. Evolutionary algorithms are used to optimize both the control and morphology of the robot to different hardware conditions and walking surfaces in the lab. To achieve this, a new gait controller concept with an adjustable complexity is introduced. This allows evolution in scenarios with a wide range of evaluation budgets. A final proof-of-concept implementation of adaptive morphology is also demonstrated. Our robot was shown to be able to adapt its body continuously while walking in different unstructured outdoor terrains, significantly outperforming a non-adaptive approach. The thesis concludes that adaptation of the physical body of a robot is feasible, and in fact, already shows significant benefits with current technology and methods. Evolutionary algorithms are shown to be effective for adaptation of morphology in a range of different conditions. By developing new methods and technology, as well as demonstrating their utility through real-world experiments, we hope to inspire others to use adaptive morphology on their physical robots.

• Chou, Jiader; Glette, Kyrre & Nygaard, Tønnes Frostad (2017). Terrain classification using 3D optical tactile sensor. Universitetet i Oslo. Full text in Research Archive Show summary

  Identifying different types of terrains is an important ability for every legged robot to achieve a stable locomotion. A variety of sensors has been applied to different robots in order to discriminate between terrains accurately. The tactile sensor has the benefits of measuring properties from terrain by physical contact between the sensor and the surface. However, the tactile sensor has rarely been utilized on quadruped robots in previous studies, and little attention has been paid to the type of sensor. There is a variety of types of tactile sensors, each with their benefits and drawbacks. The optical tactile sensor has high sensitivity, small size, light weight and low detection time, which are important properties to distinguish between different surfaces. This thesis investigates the possibility of identifying different terrains using 3D optical tactile sensors and machine learning. The measurements were retrieved from a quadruped robot developed at the University of Oslo on four different terrains. The proposed approach has the ability to classify terrains in real-time on the physical robot, and a custom segmentation method was presented for extracting desired sensor data. The segmented sensor data was the basis for creating five different feature sets and tested on five different classifiers: support vector machine, artificial neural network, naive Bayes, k-nearest neighbors, and decision tree. The experimental results demonstrated to be among the top performing approaches compared to earlier work with an accuracy of 94.8% with the support vector machine.

• Thorstensen, Mathias Ciarlo; Glette, Kyrre & Nygaard, Tønnes Frostad (2017). Visualization of Robotic Sensor Data with Augmented Reality. Universitetet i Oslo. Full text in Research Archive Show summary

  To understand a robot's intent and behavior, a robot engineer must analyze data at the input and output, but also at all intermediary steps. This might require looking at a specific subset of the system, or a single data node in isolation. A range of different data formats can be used in the systems, and require visualization in different mediums; some are text based, and best visualized in a terminal, while other types must be presented graphically, in 2D or 3D. This often makes understanding robots challenging for humans, as it can be hard to see the whole picture of the situation. This thesis attempts to solve this issue, by creating an augmented reality system on the virtual reality platform HTC Vive, to investigate methods for visualization of a robot's state and world perception. It also investigates the effect augmented reality has in increasing a user's understanding of a robot system. The visualization was achieved by projecting a robot's sensor data into the user's reality, presenting it in a intuitive way. Augmented reality was achieved by utilizing HTC Vive's front facing camera, and showing the augmented video see-through in virtual reality. To test the system's ability in increasing the user's understanding, a user study was conducted. The study tested the users' understanding of the robot's perception of its environment. This was done by comparing the augmented reality system with traditional methods. The implemented augmented reality system was successfully tested on 31 subjects in the user study. Quantitative data was recorded to measure the understanding, and a questionnaire was conducted to get qualitative data about the system. The results show a significant increase in the subjects' understanding.

• Fahle, Hans Fredrik; Fahle, Hans Fredrik; Glette, Kyrre & Nygaard, Tønnes Frostad (2017). Predicting Gaits Based on Prior Experience. Universitetet i Oslo. Full text in Research Archive

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