VIROS Sårbarheit i eit robotsamfunn

• Mahler, Tobias & Haapio, Helena (2026). Legal Informatics, Legal Technology and Legal Design: Stronger Together? I Schweighofer, Erich; Eder, Stefan; Costantini, Federico & Schmautzer, Felix (Red.), Human-Machine Cooperation in Cyberspace / Mensch-Maschine-Kooperation im Cyberspace: Proceedings of the 29th International Legal Informatics Symposium IRIS 2026. Weblaw. ISSN 9783039163236. s. 201–210. doi: https:/iris-conferences.eu/tagungband-iris26-proceedings-iris26. Fulltekst i vitenarkiv Vis sammendrag

  This paper provides an integrated mapping of legal informatics, legal technology, and legal design as complementary perspectives on the interaction between law, humans, and digital systems. It traces the development of legal informatics, contrasts it with the applied focus of legal technology, and introduces legal design as a human-centred approach concerned with goal-reaching, purpose, action, and outcomes. Rather than treating these perspectives as separate, the paper argues that they are stronger when understood as mutually reinforcing dimensions of how legal solutions can be designed and built to better meet the needs of those they are meant to serve. A potential path toward integrating all three approaches is discussed.

• Nishimura, Markus Yuki; Matsumoto, Kohei; Tørresen, Jim & Kurazume, Ryo (2026). FLexible Multi-Robot Social Navigation Using Diffusion-Based Deep Reinforcement Learning. I Ishii, Kazuo; Shibata, Tomohiro; Howard, Ayanna; Rossi, Silvia & Clodic, Aurélie (Red.), Proceedings of The 35th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2026). IEEE. ISSN 9798331588656. s. 2122–2127. doi: 10.1109/RO-MAN72286.2026.11714669. Fulltekst i vitenarkiv Vis sammendrag

  Diffusion-based reinforcement learning has recently shown strong performance in robot navigation, and prior work has demonstrated that Q-Score Matching (QSM) is effective in crowded environments. Building on this line of work, we study inference-time guidance for multi-robot social navigation using Multi-Agent Q-Score Matching (MAQSM) as the backbone policy. Rather than modifying the training objective, the proposed method steers reverse diffusion sampling of a trained MAQSM policy at evaluation time toward more coordinated multi-robot behavior. The guidance combines formation consistency and goal alignment, enabling deploymenttime control without retraining. In our implementation, robots share the same diffusion policy parameters, generate per-robot actions under this shared policy, and execute the resulting multi-robot action jointly in the simulator. Experiments first compare QSM and MAQSM to motivate the choice of MAQSM as the underlying multi-robot backbone, and then compare unguided and guided MAQSM in a more challenging bidirectional scenario. The results show that inference-time guidance improves success and safety in denser settings, at the cost of longer navigation time. These findings position post-training guidance as a practical way to improve diffusion-based multirobot policies while preserving the original learning pipeline.

• Tørresen, Jim; Lindblom, Diana Saplacan; Baselizadeh, Adel; Mahler, Tobias & Bygrave, Lee Andrew (2026). Reducing Robot Vulnerabilities Through Joint Regulatory Assessment and User-Centered Development and Testing. I Weng, Yueh-Hsuan (Red.), Social Robots and Ethical Design. Springer. ISSN 9789819225156. Fulltekst i vitenarkiv Vis sammendrag

  This book chapter introduces research examples from a unique collaboration between legal scholars and technology scholars who have together endeavored to make progress in safe and privacy-preserving robot assistant development and deployment. This collaboration has taken place within the “Vulnerability in the Robot Society” (VIROS) research project at the University of Oslo, Norway (VIROS 2025). Institutionally, this is a joint research project between the Norwegian Research Center for Computers and Law (NRCCL) at the Department of Private Law and the Robotics and Intelligent Systems (ROBIN) research group at the Department of Informatics. The project explores challenges regarding digital vulnerabilities that the adoption of robots in human environments poses, particularly as regards privacy, safety, and security, and how these challenges can be met from legal and technical perspectives. We have been particularly interested in exploring assistant and healthcare robots since this domain imposes high demands on the technology to be used. As part of the project, we have analyzed various European Union (EU) regulations that have been introduced in recent years, with a view to assessing their impact in the domain. The TIAGo robot from PAL Robotics has been the main robot platform for technical work and experimental studies in the project. A number of novel methods for robot sensing and control have been implemented. Further, several of them have been assessed through human–robot interaction studies. This chapter introduces the VIROS project and outlines some of our regulatory and technological research. We also highlight several of the conflicting trade-offs seen in the domain of HRI (Torresen et al. 2023).

• Lindblom, Diana Saplacan; Kuoppamäki, Sanna; Bodenhagen, Leon & Tørresen, Jim (2026). Robots as Welfare Technologies and Actors within Future Home and Healthcare Services. I Havinen, Laura & Hägglund, Susanne (Red.), Adjunct Proceedings of the 14th Nordic Conference on Human-Computer Interaction. Association for Computing Machinery (ACM). ISSN 9798400727986. s. 1–4. doi: 10.1145/3821402.3830201. Fulltekst i vitenarkiv Vis sammendrag

  This workshop explores whether, how, and under which conditions Welfare Robots (WRs), may be meaningfully integrated into future home- and healthcare services and practices. Building on current debates on welfare technology, AI-driven robots, and post-growth Human-Robot Interaction (HRI), the workshop invites designers, roboticists, engineers, healthcare professionals, philosophers, sociologists, and other practitioners to critically examine and systematically engage in contributing to exploring design alternatives and co-design a future model for responsible integration of robots into future care services, using Story Dialogue Method.

• Bodenhagen, Leon; Treusch, Pat; Kruger, Norbert & Lindblom, Diana Saplacan (2026). Workshop: Robociety – Vision and Reality. I Seibt, Prof. Johanna; Alami, Prof. Rachid; Chatila, Prof. Emeritus Raja; Ess, Prof. Emeritus Charles; Fischer, Prof. Kerstin & Gunkel,, Prof. David (Red.), Conference Proceedings of the Bi-Annual Conference Robophilosophy - "Connected Futures: Nature, Robots, and Society", 2026. Springer. Fulltekst i vitenarkiv Vis sammendrag

  Robociety refers to the pervasive use of interactive robots in everyday life, which today is still more a vision than a reality. It is also a name of a project [1] with the overarching aim to ”unlock the benefits that robots can bring to society - while proactively addressing the potential risks they pose”. At the workshop, we will discuss the state of the art in interactive robots and their applications in real-world environments. By identifying technical, ethical, and procedural challenges, we aim to pinpoint promising application areas as well as societally meaningful and at the same time commercially viable use cases. These could pave the way for broader integration of interactive robots into daily life.

• Lindblom, Diana Saplacan; Weng, Yueh-Hsuan; Bravo, Pedro Pablo Lucas; Baselizadeh, Adel & Tørresen, Jim (2026). A Cross-Cultural Video-Based Study between Norway and Japan on Informed Consent and Disclosure Mechanisms on the Use of Social Robots in Public and Private Spaces - Users' Perspectives. I Ishii, Kazuo; Shibata, Tomohiro; Howard, Ayanna; Rossi, Silvia & Clodic, Aurélie (Red.), Proceedings of The 35th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2026). IEEE. ISSN 9798331588656. doi: https:/ieeexplore.ieee.org/document/11714840/. Fulltekst i vitenarkiv
• Sikora, Claudia Magdalena; Otterdijk, Marieke van; Soma-Jestilä, Rebekka; Tørresen, Jim & Lindblom, Diana Saplacan (2026). "There’s something human about it!” - Exploring users’ perception of nonverbal communication of robotic furniture. I Samani, Hooman & Akhond, Saina (Red.), Proceedings of the International Confernece on Social Robotics (ICSR) + ART 2026. Springer International Publishing . ISSN 9789819267972. Fulltekst i vitenarkiv Vis sammendrag

  Non-anthropomorphic robots are integrating into our homes. People attribute human-like characteristics to these robots, although they do not resemble humans. This raises the question of whether similar processes would occur when people interact with robot furniture. Thus, the presented exploratory pilot study investigates how users intuitively interpret and perceive the non verbal communication of such robots. In an instrumental case study, we had eleven participants interacting with the T-ABLE robot through expressive behavior. Participants were interviewed about their experience. Our findings indicate that the participants use their associations between behavior and prior to similar experiences to attribute personality to the robot table. These findings provide insights for theorizing the intuitive comprehension of the behavior of non-anthropomorphic robots.

• Sarfraz, Burhan Mohammad; Lindblom, Diana Saplacan; Baselizadeh, Adel & Torresen, Jim (2026). The Privacy-Preserving Capabilities of a Service Robot in a Scenario-Based Healthcare Setting. I Baillie, Lynne; Smart, William D.; Graaf, Maartje De; Gombolay, Matthew & Torre, Ilaria (Red.), Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction (HRI Companion '26). Association for Computing Machinery (ACM). ISSN 9798400723216. s. 675–679. doi: 10.1145/3776734.3794481. Fulltekst i vitenarkiv
• Earls, Davis, Peter Alexander; Mateo, Aboy,; Bygrave, Lee Andrew; Timo, Minssen,; Urs, Gasser, & Corrales, Compagnucci, Marcelo (2026). EU Cybersecurity Regulation in the Quantum Age. I Aboy, Mateo; Compagnucci, Marcelo Corrales & Minssen, Timo (Red.), Quantum Technology Governance I: Law and Regulation. Springer Nature. ISSN 9789819583713. s. 149–179. doi: 10.1007/978-981-95-8371-3_5. Fulltekst i vitenarkiv Vis sammendrag

  This chapter explores the intersection of quantum computing and European Union (EU) cybersecurity law. It examines to what extent cybersecurity regulation in the EU is fit-for-purpose to deal with the challenges of quantum computing. Two key challenges are identified: (i) harvest now, decrypt later (HNDL) attacks, and (ii) the accelerated development of quantum computers outpacing current cybersecurity measures. The chapter argues that concepts like “state of the art” and “appropriate technical and organizational measures” characteristic of EU cybersecurity law fail to sufficiently account for cybersecurity threats anticipated to materialize in the future, but impacting networks and information systems today. Proposed solutions include enhancing judicial clarity of technical cybersecurity requirements, increasing policy focus on post-quantum cryptography, adopting firmer cybersecurity requirements in hard law, and shifting towards alternative terms that properly account for future cybersecurity uncertainties. The chapter concludes by advocating for proactive regulatory approaches anchored in anticipatory governance and multi-layered strategies to safeguard against the quantum threat.

• Lintvedt, Mona Naomi (2026). Privacy Regulation in Japanese Robotics: Conformity with EU Market Requirements. Oslo Law Review. 12(1), s. 1–30. doi: 10.18261/olr.13.1.1. Fulltekst i vitenarkiv Vis sammendrag

  This article examines the privacy regulatory framework for smart robotics in Japan and compares it with EU regulations to provide insights into EU law. It identifies disparities that could pose privacy risks, particularly as Japanese robots enter the EU market. A key concern is the absence of requirements for manufacturers to integrate privacy by design into their products, potentially resulting in robots lacking essential privacy-preserving features. The article underscores the importance of a holistic approach to safeguarding privacy in human-robot interactions, which should encompass data protection laws, product safety and cybersecurity regulations. This article reveals the fragmented and complex nature of EU legislation relevant for privacy in robotics. This poses significant risks and challenges, particularly in addressing the convergence of emerging technologies in smart robotics, whether they are imported or made in the EU.

• Pich, David; Baselizadeh, Adel; Tørresen, Jim & Miura, Jun (2025). Privacy-Preserving Machine Learning-Based In-Bed Sleep Posture Monitoring Using Wi-Fi Signals. I Benallegue, Abdelaziz (Red.), 2025 13th International Conference on Control, Mechatronics and Automation (ICCMA). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331591410. doi: 10.1109/iccma67641.2025.11369717.
• Paulsen, Geir; Cardenas, Juan Sebastian; Alsgaard, Rosa Nicoline Pham; Baselizadeh, Adel; Uddin, Md Zia & Tørresen, Jim (2025). AI-Based User Gesture Recognition for Human-Robot Interaction Using Wrist Sensors. I Kita, Eisuke (Red.), 2025 11th International Conference on Robotics and Artificial Intelligence (ICRAI), December 19-21, 2025, Nagoya, Japan. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331590680. s. 161–165. doi: 10.1109/icrai68431.2025.11396715. Fulltekst i vitenarkiv Vis sammendrag

  Natural and intuitive interaction remains a central challenge in human-robot communication. This study presents a privacy-preserving gesture recognition framework that enables command-based interaction through simple hand and arm movements. Motion data are captured using a wrist-worn sensor, eliminating the need for cameras or other intrusive tracking systems. Data from ten participants performing seven gesture classes, including move forwards, move backward, move left-right, spin horizontally, spin vertically, wave, and move up-down are used to train and validate a hybrid Convolutional Long Short-Term Memory (CNN-LSTM) model. An additional non-command state is included to ensure the robot remains inactive when no gesture is detected. The proposed model achieves an overall recognition accuracy of approximately 95% across all gesture classes using cross-validation. This framework enhances the safety, intuitiveness, and fluidity of human-robot interaction and provides a robust foundation for gesture-based robot control and human activity recognition.

• Tønnessen, Håkon Haustreis; Uddin, Md Zia & Tørresen, Jim (2025). PINE: Planning and Identifying Neural Network for Thinking Fast and Slow. I Kita, Eisuke (Red.), 2025 11th International Conference on Robotics and Artificial Intelligence (ICRAI), December 19-21, 2025, Nagoya, Japan. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331590680. s. 191–197. doi: 10.1109/icrai68431.2025.11396706. Fulltekst i vitenarkiv Vis sammendrag

  The human brain's unique ability to seamlessly switch between quick, effortless reactions and slow, deliberate thinking forms the foundation for the content of this paper. Humans effortlessly navigate complex tasks like walking, speaking, and driving, relying on heuristic responses to their environment. This natural division of labor allows humans to adapt quickly and efficiently, tackling both new challenges and familiar tasks. Drawing inspiration from this cognitive duality, we propose, in this paper, a machine-based analog that employs a two-level functionality mirroring human capabilities. The approach centers on a Reinforcement Learning agent that replicates human learning through trial and error. The thesis introduces the Planning and Identifying Neural Network (PINE), a framework that identifies tasks using a combination of inherited environmental information, observations, and human-readable task descriptors. PINE leverages a model-based Reinforcement Learning algorithm, streamlining agent complexity and significantly reducing solution-finding time compared to model-free algorithms. PINE operates in real-time, utilizing initial environmental observations and task descriptors to identify and categorize encountered tasks. For unknown tasks, PINE employs meta-learning, selecting the most similar known task to expedite the solution-finding process with fewer episodes. Despite the challenge of task identification without interaction or labels, PINE demonstrates high accuracy in recognizing previously solved tasks and providing reliable estimates for the most similar tasks. This innovative two-level learning model represents a significant step towards creating adaptive machines that efficiently handle both familiar and novel challenges.

• Baselizadeh, Adel; Uddin, Md Zia; Khaksar, Weria; Lindblom, Diana Saplacan & Tørresen, Jim (2025). Privacy-Preserving 3D Lidar-Based Multi-Modal Activity Recognition in Human-Robot Interaction. International Conference on Control, Mechatronics and Automation. ISSN 2837-5114. 2025, s. 516–523. doi: 10.1109/iccma67641.2025.11369549. Fulltekst i vitenarkiv Vis sammendrag

  Human activity recognition (HAR) involves using sensors to collect human data, which is then analyzed to identify their activities. HAR has numerous applications across various fields. One significant area is human-robot interaction (HRI). Recognizing user activities provides robots with valuable insights into the user’s status, enhancing the efficiency of HRI. However, developing HAR models presents privacy challenges due to the collection of user data, especially in robots, which are often equipped with diverse sensors. This paper proposes privacy-preserving HAR methods within the context of HRI.The paper investigates using privacy-preserving sensors, with a particular focus on 3D Lidar, to develop HAR models. It explores the integration of 3D Lidar with other sensors, including user-wearable sensors and robot-based sensors, including force/torque sensors, through multimodal deep learning (DL) approaches. Various DL-based sensor fusion methods, including data-level and feature-level fusion approaches, are thoroughly examined, and their accuracies for HAR are compared.A novel dataset was collected to train the multimodal DL models, capturing various user activities during HRI. This dataset leverages 10 different sensors, including 9 privacy-preserving sensors, along with an RGB camera for reference. The paper considers nine distinct user activities, including physical interactions with a robot and commanding a robot to perform specific tasks. The results indicate that integrating the sensors’ data at the feature-level achieves an 80.73% accuracy in recognizing various user activities during HRI.

• Santos, Letícia dos; Tørresen, Jim; Kolberg, Mariana & Maffei, Renan (2025). An Autonomous Floor Clearing Strategy to Tidy up Unknown Home Environments with a Mobile Manipulator Robot. I Slawiñski, Emanuel; García, Cecilia & Tosetti, Santiago (Red.), 2025 IEEE International Conference on Advanced Robotics (ICAR). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331578107. doi: 10.1109/icar65334.2025.11338715. Fulltekst i vitenarkiv
• Torresen, Jim; Laschi, Cecilia; Prestes, Edson; Kavraki, Lydia E.; Caleb-Solly, Praminda & Weng, Yueh-Hsuan (2025). Robot Ethics: Ethical, Legal, and User Perspectives in the Development and Application of Robotics and Automation [From the Guest Editors]. IEEE robotics & automation magazine. ISSN 1070-9932. 32(4), s. 11–11. doi: 10.1109/mra.2025.3619589. Fulltekst i vitenarkiv
• Pham, Hoang Minh; Noori, Farzan Majeed; Uddin, Md Zia & Tørresen, Jim (2025). Heart Rate Forecasting Using Ultra-Wideband Radar with Sequence-to-Sequence Model. I Cruz, Luis; Loncaric, Sven; Chen, Zhibo; Pinho, Armando J.; Batista, Jorge & Subasic, Marko (Red.), Proceedings of the 14th International Symposium on Image and Signal Processing and Analysis (ISPA), Coimbra, Portugal, October 29-31, 2025. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331577551. s. 16–21. doi: 10.1109/ispa66905.2025.11259452. Fulltekst i vitenarkiv Vis sammendrag

  Heart dysfunction can be very dangerous and directly associated with the risk of fatality. Therefore, automatic heart rate monitoring is important for detecting a heart abnormality early and providing timely intervention. The development of advanced sensor technology allows continuous tracking of the heart rate, as well as providing more health-related data sources, which could further improve the forecasting performance. In this study, we investigate the use of recent heart rate values and Ultra-Wideband (UWB) data in the last 20s to predict the next 10s of heart rate. Data were collected from 20 participants performing different activities. We examine the forecasting by using only a heart rate sensor (uni-modality) and by using heart rate sensor and UWB together (multi-modality). Three levels of activity were included in the study: resting (rest), lying after doing exercises (lying-abnormal) and lying after full recovery (lying-normal). A multi-modality Sequence-to-Sequence (Seq2Seq) model has a 10-percent quantile losses of 5.20 for rest activity, 4.92 for lying-abnormal activity, and 4.24 for lying-normal activity. With the lowest loss, Seq2Seq outperforms Autoregressive Integrated Moving Average (ARIMA), Error Trend and Seasonality (ETS), Transformer and Temporal Fusion Transformer (TFT) in forecasting heart rate in the three activity levels. Our results point to a new direction in multimodal prediction of heart rate to assist healthcare, using deep learning approaches.

• Goka, Shunsuke; Strand, Ørjan; Miura, Jun & Tørresen, Jim (2025). Situation-Based Navigation Strategy Switching for Mobile Robots in Dynamic Pedestrian Environments. I Uchiya, Takahiro; Nishimura, Ryota & Ikehara, Tadaaki (Red.), 2025 IEEE 14th Global Conference on Consumer Electronics (GCCE). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331524166. doi: 10.1109/gcce65946.2025.11275115. Fulltekst i vitenarkiv Vis sammendrag

  This paper proposes a method for adaptively switching navigation strategies based on a visual assessment of the current situation. Despite recent progress in motion planning and navigation methods, it is still challenging to adopt a single navigation method in various situations, which are determined by both the environment structure and pedestrian distribution and movements. A promising approach is to switch between multiple navigation strategies depending on the current situation. The proposed method adopts a visual situation classification, trained on an automatically labeled dataset, for choosing an appropriate local motion planner. Experimental comparison with fixed planners using a real robot demonstrates the superiority of our method in terms of both navigation efficiency and safety.

• Bygrave, Lee Andrew & Schmidt, Rebecca (2025). Regulating Non-High-Risk AI Systems Under the EU’s Artificial Intelligence Act, with Special Focus on the Role of Soft Law. I Raposo, Vera (Red.), The European Artificial Intelligence Act: Promises and Perils? | SpringerLink. Springer Nature. ISSN 9783031984068. s. 181–210. Fulltekst i vitenarkiv Vis sammendrag

  The remit of this chapter is twofold. First, it provides a concise overview of how the EU’s Artificial Intelligence Act regulates non-high-risk AI systems. Second, the chapter elucidates the role that the Act assigns to codes of practice and codes of conduct for governing these systems.

• Moghaddam, Emil Engelstad; Uddin, Md Zia; Miura, Jun & Tørresen, Jim (2025). A Robust Approach for Motion Skill-Based Scene Categorization. I Neri, Filippo (Red.), Proceedings of the 2025 10th International Conference on Machine Learning Technologies (ICMLT), May 23-25, 2025, Helsinki, Finland. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331536725. s. 482–487. doi: 10.1109/icmlt65785.2025.11193163. Fulltekst i vitenarkiv Vis sammendrag

  This paper introduces a novel method for autonomous navigation of mobile robots, combining functional scene categorization with tailored navigation strategies. Scene categorization is a computer vision task that identifies environmental types in images. Our approach establishes a taxonomy for scene categorization with the aim of utilization in mobile robots. We used a motion-skill dataset for training different neural networks. The dataset, comprising 19923 images with nine navigation strategy labels, demonstrated the feasibility of coupling environment recognition with neural networks. Three architectures (ResNet-50, BEiT-Base, ConvNeXt-Tiny) achieved notable performance, with ConvNeXt-Tiny leading with a weighted F1 score of 0.934. Pre-training on the SUN397 dataset significantly improved the model performance, emphasizing the importance of leveraging existing scene categorization datasets. This study highlights the synergy between scene categorization and functional scene categorization, providing insights for designing efficient, context-aware autonomous navigation systems.

• Rolfsjord, Sigmund Johannes Ljosvoll; Fatima, Safia; Arnim, Hugh Alexander von & Baselizadeh, Adel (2025). Multimodal Transfer Learning for Privacy in Human Activity Recognition. I Emilia, Barakova,; Ben, Allouch, Somaya; Kazuhiro, Nakadai, & Goldie, Nejat, (Red.), Proceedings of the IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) 2025. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331587710. s. 15–20. doi: 10.1109/ro-man63969.2025.11217600. Fulltekst i vitenarkiv Vis sammendrag

  IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed. The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.

• Meijer, Frida; Lindblom, Diana Saplacan; Baselizadeh, Adel & Tørresen, Jim (2025). "The wooden gripper was warmer and made the robot less threatening"– A Study on Perceived Safety based on Robot Gripper’s Visual and Tactile Properties. I Emilia, Barakova,; Ben, Allouch, Somaya; Kazuhiro, Nakadai, & Goldie, Nejat, (Red.), Proceedings of the IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) 2025. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331587710. s. 1091–1098. doi: https:/ieeexplore.ieee.org/document/11217775. Fulltekst i vitenarkiv Vis sammendrag

  An ageing population and the need of providing adequate care have led to developing robots to relieve healthcare workers and to assist individuals in their own homes. However, the successful integration of robots in such settings relies on more than just ensuring physical safety associated with physical risks (e.g., collisions): it also requires the user’s perceived safety – the users perceiving the robot as not doing any harm. This paper explores the potential influence of a robot grippers’ visual and tactile properties, such as materials and texture, on the users’ perceived safety and comfort of human-robot interaction. An initial survey was distributed to 53 participants, exploring five (n=5) robot gripper designs focusing on the robots’ gripper shape. One design shape was thereafter selected to be constructed as a cover to be placed over the parallel grippers of the TIAGo robot, by using 1) wood filament and 2) plastic. The covers were then tested in an experimental setting with 11 participants. The covers were attached to the TIAGo mobile manipulator robot and participants interacted with both of the designed gripper covers within a controlled laboratory environment. A questionnaire was distributed to all 11 experiment participants, at different stages of the interactions. The findings indicate that the material of the gripper influenced participants’ sense of comfort, familiarity, and perceived capabilities of the robot. The study suggests that perceived safety in human-robot interaction (HRI) is shaped not only by physical factors but also by how materials are personally and contextually interpreted. To better support safe and comfortable interactions, further research is needed to understand how material choices shape users’ perceived safety.

• Otterdijk, Marieke van; Neggers, Margot; Torresen, Jim & Barakova, Emilia (2025). Exploring Human Attribution of Emotional Intent to Motion Features in a Humanoid Robot. I Palinko, Oskar; Bodenhagen, Leon; Cabibihan, John-John; Fischer, Kerstin; Šabanović, Selma; Winkle, Katie; Behera, Laxmidhar; Ge, Shuzhi Sam; Chrysostomou, Dimitrios; Jiang, Wanyue & He, Hongsheng (Red.), Social Robotics. Springer. ISSN 9789819635184. s. 323–323. doi: 10.1007/978-981-96-3519-1_29. Fulltekst i vitenarkiv
• Maeda, Ryuichi; Baselizadeh, Adel; Watanabe, Shin; Kurazume, Ryo & Tørresen, Jim (2025). Adaptive Tidying Robots: Learning from Interaction and Observation. I Asfour, Tamim; Ramírez-Amaro, Karinne; Kim, Joohyung & Cheng, Gordon (Red.), 2025 IEEE/SICE International Symposium on System Integration (SII). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331531614. s. 185–192. doi: 10.1109/sii59315.2025.10871003. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Risk Narrative: Deconstructing the AIA’s Risk-Based Approach as a Regulatory Heuristic. I Raue, Benjamin; Ungern-Sternberg, Antje von; Kumkar, Lea Katharina & Rüfner, Thomas (Red.), Artificial Intelligence and Fundamental Rights. Verein für Recht und Digitalisierung e.V.. ISSN 9783565013197. s. 57–74. doi: 10.25353/UBTR-DAB1-9B5C-1EC6. Fulltekst i vitenarkiv Vis sammendrag

  While the European Union's Artificial Intelligence Act (AIA) is presented as a landmark "risk-based" framework, this article argues that its reliance on risk levels functions more as a narrative device than a consistently applied methodology. Although the AIA genu-inely engages with the concept of risk, it does so through a patchwork of distinct legislative strategies that often construe and operationalize risk in divergent ways. Examining the AIA's structure reveals that the widely used risk pyramid, while serving a crucial heuristic function in policy communication, only partly reflects the law's underlying legal architec-ture. The AIA primarily establishes two distinct risk-based categories: high-risk AI systems and general-purpose AI models presenting systemic risk, which operate under different regulatory logics. To understand the AIA’s regulatory architecture, the article traces the origins of the risk-based approach and distinguishes between risk regulation and risk-based regulation. It finds that divergent interpretations of risk by lawmakers, enforce-ment bodies, and regulated entities, coupled with the introduction of general-purpose AI models as a separate regulatory object, undermine the coherence of a singular risk-based framework, leading to what the article terms a "risk-regulatory cacophony."

• Otterdijk, Marieke van; Laeng, Bruno; Lindblom, Diana Saplacan; Baselizadeh, Adel & Tørresen, Jim (2025). Seeing Meaning: How Congruent Robot Speech and Gestures Impact Human Intuitive Understanding of Robot Intentions. International Journal of Social Robotics. ISSN 1875-4791. 17, s. 2279–2292. doi: 10.1007/s12369-025-01271-0. Fulltekst i vitenarkiv Vis sammendrag

  Social communication between humans and robots has become critical as a result of the integration of robots into our daily lives as assistants. There is a need to explore how users intuitively understand the behavior of a robot and the impact of social context on that understanding. This study measures mental effort (as indexed by pupil response) and processing time, measured as the time taken to provide the correct answer, to investigate participants’ intuitive understanding of the robot’s gestures. Thirty-two participants participated in a charades game with a TIAGo robot, during which their eyes were tracked. Our findings show a relationship between mental effort and processing time, and indicate that robot gestures, congruence of speech and behavior, and the correctness of interpreting robot behavior influence intuitive understanding. Furthermore, we found that people focused on the robot’s limb movement. Using these findings, we can highlight what features contribute to the intuitive interaction with a robot, thus improving its efficiency.

• Weng, Yueh-Hsuan; Torabi, David; Tørresen, Jim; Dong, Zonghao & Hirata, Yasuhisa (2025). Bridging Ethics and Reality: Integrating Thought Experiments and Empirical Insights in Robot Ethics. IEEE robotics & automation magazine. ISSN 1070-9932. 32(4), s. 84–90. doi: 10.1109/mra.2025.3584352. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Privacy and Data Protection. I Kaufmann, Mareile & Lomell, Heidi Mork (Red.), De Gruyter Handbook of Digital Criminology. De Gruyter Brill. ISSN 9783111061931. s. 381–388. doi: 10.1515/9783111062037-044. Fulltekst i vitenarkiv Vis sammendrag

  The chapter elucidates the semantics of privacy and data protection, taking account of transnational variations in how they are understood. Their interrelationship is also explained as is their relationship to closely linked concepts, such as data security and bio-privacy. Finally, the chapter briefly canvasses legal and social norms for safeguarding privacy and personal data.

• Lintvedt, Mona Naomi (2025). Under the Robot's Gaze. Law, Innovation and Technology. ISSN 1757-9961. 17(1), s. 139–158. doi: 10.1080/17579961.2025.2469346. Fulltekst i vitenarkiv Vis sammendrag

  This article delves into the power dynamics at play in human–robot interactions, using gaze theory and panopticism to argue that social robots exert a form of disciplinary power over humans. It challenges the notion of gaze as merely visual by highlighting the sensory and psychological dimensions of omnipresent surveillance that robots are capable of. Social robots, with their advanced sensory capabilities, can exert a form of disciplinary power over humans, leading to a power imbalance in the robot–human relationship. The EU’s regulatory approach to robotics is insufficient, focusing too narrowly on specific functionalities and not addressing the broader impacts of robots’ interactive presence in human environments. The article calls for a more comprehensive regulatory framework that recognises and addresses the complex power relationships inherent in our interactions with robots.

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• Raposo, Vera (2025). The European Artificial Intelligence Act: Promises and Perils? | SpringerLink. Springer Nature. ISBN 9783031984068. 589 s. doi: 10.1007/978-3-031-98406-8. Fulltekst i vitenarkiv Vis sammendrag

  This book provides one of the first in-depth examinations of the EU AI Act in its final form gathering contributions from leading experts in the field.

Sjå alle arbeida i NVA

• Mahler, Tobias (2026). Artificial intelligence and robotics as long problems. Fulltekst i vitenarkiv
• Mahler, Tobias (2026). When are Marine Navigation Systems High-risk AI systems Under the AI Act? Fulltekst i vitenarkiv
• Schwemer, Sebastian Felix & Mahler, Tobias (2026). The DSA and the AI ecosystem: search and information retrieval revisited. doi: https:/dsa-observatory.eu/conference-2026/. Fulltekst i vitenarkiv
• Tørresen, Jim (2026). Tutorial: Ethics in Embedded Systems and Robots. Fulltekst i vitenarkiv
• Tørresen, Jim (2026). Embedding Intelligence in Robots Through Interdisciplinary Collaboration. Fulltekst i vitenarkiv
• Tørresen, Jim (2026). 2nd Workshop on Robot Ethics – Ethical, Legal and User Perspectives in Robotics and Automation (WOROBET). Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan; Kuoppamäki, Sanna; Bodenhagen, Leon & Tørresen, Jim (2026). Presentation during Workshop at NordiCHI 2026 at the 1st Workshop on Robots as Welfare Technologies and Actors within Future Home- and Healthcare Services: Co-Designing an Integration Model through Story-Dialogue Method. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2026). Presentation at the Robophilosophy Conference: Robots as Welfare Technologies in Home and Healthcare - Some of the Lessons Learned So Far. doi: https:/www.ucd.ie/robophilosophy2026/workshops/robociety-visionandreality/. Fulltekst i vitenarkiv Vis sammendrag

  he talk will present some of the lessons learned so far in some of the previous or ongoing research projects (Vulnerabilities in Robot Society-VIROS, Predictive and Intuitive Robot Companion – PIRC, and ROBOWELL- Robots as Welfare Technologies and Actors for Elderly Care). It addresses, amongst others, some of the practical and ethical challenges of integrating social robots, as actors, within care environments, seen from the user perspectives (e.g., elderly, healthcare professionals). These practical examples and ethical challenges, in their turn, will eventually lead to the more complex societal and philosophical questions about if and when, and how social robots or socially assistive robots would be appropriate to be integrated within home- and healthcare. The talk also aims to raise questions about looking at advanced (AI-based) social robots as an integrated part of a larger (healthcare or societal) system, rather than looking at these as isolated technological entities often used in single-use cases or experiments.

• Lindblom, Diana Saplacan (2026). A Cross-Cultural Video-Based Study between Norway and Japan on Informed Consent and Disclosure Mechanisms on the Use of Social Robots in Public and Private Spaces - Users' Perspectives. doi: https:/ro-man2026.org/program-at-a-glance/. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2026). Mapping the Maze of EU Cybersecurity Regulation. Fulltekst i vitenarkiv
• Melteig, Elina & Lintvedt, Mona Naomi (2026). Når roboten har øyne, endrer vi adferd. [Internet]. forskning.no. Fulltekst i vitenarkiv Vis sammendrag

  De fleste oppfører seg litt annerledes sammen med andre. Dette gjelder også når vi vet eller mistenker at vi blir sett, selv av en robot.

• Sikora, Claudia Magdalena; Lindblom, Diana Saplacan & Tørresen, Jim (2026). Presentation of accepted paper: “There’s something human about it!” - Exploring users’ perception of nonverbal communication of robotic furniture. doi: https:/icsr2026.uk/programme/. Fulltekst i vitenarkiv Vis sammendrag

  Non-anthropomorphic robots are integrating into our homes. People attribute human-like characteristics to these robots, although they do not resemble humans. This raises the question of whether similar processes would occur when people interact with robot furniture. Thus, the presented exploratory pilot study investigates how users intuitively interpret and perceive the non verbal communication of such robots. In an instrumental case study, we had eleven participants interacting with the T-ABLE robot through expressive behavior. Participants were interviewed about their experience. Our findings indicate that the participants use their associations between behavior and prior to similar experiences to attribute personality to the robot table. These findings provide insights for theorizing the intuitive comprehension of the behavior of non-anthropomorphic robots.

• Lindblom, Diana Saplacan; Kuoppamäki, Sanna; Bodehagen, Leon & Tørresen, Jim (2026). Webpage for 1st Workshop on Robots as Welfare Technologies and Actors within Future Home- and Healthcare Services: Co-Designing an Integration Model through Story-Dialogue Method ROBOWELL. doi: https:/sites.google.com/view/robowell-nordichi26/home?pli=1&authuser=1. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan; Prestes, Edson; Caleb-Solly, Praminda & Takahashi, Toshie (2026). Diversity and International Perspectives. doi: https:/sites.google.com/view/icra2026-workshop-robot-ethics/home/programme?authuser=1. Fulltekst i vitenarkiv
• Tørresen, Jim; Lindblom, Diana Saplacan; Prestes, Edson; Schweighofer, Erich; Caleb-Solly, Praminda & Weng, Yueh hsuan (2026). 2nd ICRA 2026 Workshop on Robot Ethics Ethical, Legal and User Perspectives in Robotics & Automation WOROBET. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2026). Presentation of ROBOWELL research project during MishMash launch. doi: https:/mishmash.no/events/aulaen2026/. Fulltekst i vitenarkiv
• Kuoppamäki, Sanna; Lindblom, Diana Saplacan & Pauletto, Sandra (2026). Presentation at the Welfare Technology Fair. Fulltekst i vitenarkiv
• Kuoppamäki, Sanna; Lindblom, Diana Saplacan; Pauletto, Sandra & Lu, Tien-Ying (2026). Exhibition at the Welfare Technology Fair. Fulltekst i vitenarkiv
• Lintvedt, Mona Naomi (2026). Disrupting privacy: Our not-so-private lives with robots. doi: https:/youtu.be/RX8okOAoRHQ. Fulltekst i vitenarkiv Vis sammendrag

  Robots have long captured our imagination, and many real-world designs borrow from popular culture. While they were originally intended to perform dull, dangerous and dirty tasks, most non-industrial robots today are made to be companions — acting more like friends than tools. Social robots can become part of our private and intimate lives, affecting our physical and psychological well-being and challenging our right to privacy. That close human–robot interaction creates privacy risks that go beyond data privacy. Privacy is more than control over data; it also covers autonomy, personal development, the ability to establish relationships and the right to be left alone. Whether intentional or not, robots can deceive, manipulate or foster emotional attachment in their interactions with people. In this talk, Naomi will give some examples on how social robots can intrude on our privacy and suggest ways to reduce the risk.

• Hjort, Live Sunniva (2026). EU endrer sine prioriterte KI-verdier og skaper rettslig usikkerhet. doi: https:/rett24.no/articles/eu-endrer-sine-prioriterte-ki-verdier-og-skaper-rettslig-usikkerhet. Fulltekst i vitenarkiv Vis sammendrag

  I en verden hvor teknologigigantene får stadig mer makt og EU viser tendens til knefall for KI-industrien, må Stortinget sette tydelige rammer.

• Lintvedt, Mona Naomi (2026). Generative AI, Privacy & Robotics. Fulltekst i vitenarkiv
• Lintvedt, Mona Naomi (2026). Roboter - fra verktøy til bestevenn? Fulltekst i vitenarkiv Vis sammendrag

  Roboter har utviklet seg fra å være maskiner som utfører repetitive oppgaver i industrien til å innta våre hverdagsliv, som for eksempel robotstøvsugere og -gressklippere. Flere av de store techselskapene satser nå på robotikk. Denne utviklingen har vært drevet av lovnaden om at roboter skal ta seg av kjedelige, skitne og farlige jobber slik at mennesker kan bruke tid på mer kreative og meningsfulle aktiviteter. I realiteten er mange roboter dårlige til å utføre oppgaver, mens de er designet med utseende og adferd som appellerer til menneskelige følelser. Dette innlegget vil ta opp hvorfor det kan være nødvendig å regulere sosiale roboter for å unngå skadelig manipulering og emosjonell tilknytning i relasjonen mellom mennesker og roboter

• Tørresen, Jim (2025). Presentation as a panelist at a panel on global perspectives on AI development and policy. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). Industrial AI Center Partner Presentation. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). How should Robot Assistants behave? Fulltekst i vitenarkiv
• Tørresen, Jim (2025). From Adaptation of the Robot Body and Brain Using Rapid-Prototyping to Human–Robot Interaction with TIAGo. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2025). A Cross-Cultural Study between Norway and Japan on Consent in HRI. doi: https:/2025.roboethics.design/program. Fulltekst i vitenarkiv
• Melteig, Elina; Lintvedt, Mona Naomi & Tørresen, Jim (2025). Selv luftmåleren kan avsløre en hjemmefest. Derfor er roboter i hjemmet perfekte verktøy for overvåkere. - Titan.uio.no. [Internet]. Titan.uio.no. doi: https:/www.titan.uio.no/teknologi/2025/roboter-i-hjemmet-utfordrer-personvernet.html. Fulltekst i vitenarkiv Vis sammendrag

  – Uavhengig av hva som er intensjonen, får man mindre privatliv med roboter i hjemmet, sier forsker. Men det finnes noen råd for bedre personvern. 

• Lintvedt, Mona Naomi (2025). AIA og GDPR: Som olje og vann? doi: https:/www.jus.uio.no/ifp/om/organisasjon/seri/arrangementer/2025/personvernkonferansen-2025.html. Fulltekst i vitenarkiv
• Lintvedt, Mona Naomi (2025). Åpnet muligheter for fremtiden - Universitetet i Innlandet. [Internet]. Universitetet i Innlandet. doi: https:/www.inn.no/studier/studenthistorier/juss-psykologi-og-samfunnsfag/speedating-for-jusstudenter/index.html. Fulltekst i vitenarkiv Vis sammendrag

  Tidenes første Speed-Networking for jusstudenter er ble en suksess da det ble arrangert på Lillehammer for første gang.

• Melteig, Elina & Lintvedt, Mona Naomi (2025). Er algoritmestyrt velferd en fattigdomsfelle? - Titan.uio.no. [Internet]. Titan.uio.no. doi: https:/www.titan.uio.no/teknologi/2025/digitalisering-og-ki-er-algoritmestyrt-velferd-en-.html. Fulltekst i vitenarkiv Vis sammendrag

  – Store KI-skandaler i europeiske land viser tydelig hvilke skader feil bruk av kunstig intelligens kan gjøre. Særlig overfor sårbare grupper, sier forsker Naomi Lintvedt.

• Lindblom, Diana Saplacan (2025). Presentation: ROBOts as Welfare Technologies and Actors for ELderLy Care: A Nordic Model for Integration of Advanced Assistive Technologies (ROBOWELL) pre-kickoff. Fulltekst i vitenarkiv Vis sammendrag

  ROBOWELL - meeting with the project partners (UiO, KTH, SDU)

• Hjort, Live Sunniva (2025). A Patient Rights Perspective on Explainability in Healthcare: Is the Patient in the Dark? Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan & Murashova, Natalia (2025). AI in Society: Virtual and Physical AI. doi: https:/www.uio.no/om/samarbeid/skole/fagped-dag/program.html. Fulltekst i vitenarkiv Vis sammendrag

  This talk explores the evolving landscape of artificial intelligence in various societal contexts, focusing on the integration and implications of AI (virtual) tools such as e.g., ChatGPT, Microsoft Copilot, but also the use of "physical AI", such as in social robots. It showcases practical cases, showing some insights from our initial fieldwork applying the Ethical Risk Assessment of AI in practice (ENACT) in various private and public (learning) organizations, as well as some insights from our work within Human-Robot Interaction and social robots area in the Vulnerability in Robot Societies (VIROS), Predictive and Intuitive Robot Companion (PIRC) research projects, and our recently funded ROBOts as Welfare Technologies and Actors for ELderLy Care: A Nordic Model for Integration of Advanced Assistive Technologies (ROBOWELL) project.

• Lindblom, Diana Saplacan (2025). A Cross-Cultural Study between Norway and Japan on Consent in HRI; The Use of Social Robots in Public and Private Spaces – Users’ Perspectives. doi: https:/2025.roboethics.design/program. Fulltekst i vitenarkiv
• Tørresen, Jim; Prestes, Edson; Caleb-Solly, Praminda; Weng, Yueh Hsuan & Watanabe, Shin (2025). CASE 2025 Workshop on Ethical Considerations in Robotics and Automation (WECRA). doi: https:/sites.google.com/view/robot-ethics-case2025-workshop. Fulltekst i vitenarkiv
• Mahler, Tobias & Tørresen, Jim (2025). VIROS in a Nutshell. doi: https:/www.jus.uio.no/ifp/english/research/projects/nrccl/viros/events/seminars/vulnerability-in-the-robot-society-final-conferenc.html. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). Keynote: Techno-Ethical Considerations when Applying Machine Learning in Real-world Systems. doi: https:/www.icmlt.org/2025.html. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). Invited talk: Intelligent Robotics in Healthcare. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). Guest lecture: Intelligent Robotics in (Home) Healthcare. Fulltekst i vitenarkiv
• Tørresen, Jim (2025). Invited talk: When will a robot treat us instead of a medical doctor? doi: https:/www.uio.no/english/research/strategic-research-areas/life-science/norway-life-science-conference/. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2025). Panel Debate on Ethical Risk Assessment of AI in Practice. doi: https:/www.nora.ai/events/2025/enact-etisk-risikovurdering-av-kunstig-intelligens.html. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2025). Overview of my research: background, results, experiences, publications and future directions. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2025). "The Wooden Gripper Was Warmer and Made the Robot Less Threatening"– a Study on Perceived Safety Based on Robot Gripper’s Visual and Tactile Properties. Fulltekst i vitenarkiv
• Lindblom, Diana Saplacan (2025). Robots in Home and Healthcare Settings: Empirical and Design Perspectives. Fulltekst i vitenarkiv Vis sammendrag

  Presentation during Vulnerability in Robot Society Final Conference, June 2025

• Lindblom, Diana Saplacan (2025). Panelist during Panel Discussion: Teaching Robotics in Light of Cross-Disciplinary Challenges. Fulltekst i vitenarkiv
• Lintvedt, Mona Naomi (2025). Roboter - verktøy eller bestevenn? doi: https:/nfje.no/?tribe_events=forum-rettsinformatikk-2025. Fulltekst i vitenarkiv Vis sammendrag

  Roboter har utviklet seg fra å være maskiner som utfører repetitive oppgaver i industrien til å innta våre hverdagsliv, som for eksempel robotstøvsugere og -gressklippere. Flere av de store techselskapene satser nå på robotikk. Denne utviklingen har vært drevet av lovnaden om at roboter skal ta seg av kjedelige, skitne og farlige jobber slik at mennesker kan bruke tid på mer kreative og meningsfulle aktiviteter. I realiteten er mange roboter dårlige til å utføre oppgaver, mens de er designet med utseende og adferd som appellerer til menneskelige følelser. Dette innlegget vil ta opp hvorfor det kan være nødvendig å regulere sosiale roboter for å unngå skadelig manipulering og emosjonell tilknytning i relasjonen mellom mennesker og roboter.

• Mahler, Tobias (2025). KI-forordningen: Hvordan jobbe med risikobasert tilnærming når risiko er ukjent? Fulltekst i vitenarkiv
• Mahler, Tobias (2025). KI og mulighetsrommet — i et rettslig perspektiv. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Robots, Humans and the Law. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Risikovurdering etter AI Act. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Robot safety and beyond. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Robotics as a long problem. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Bør alle KI lover være risikobaserte? Fulltekst i vitenarkiv
• Mahler, Tobias (2025). EU perspectives on the safety of home robots. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). KI forordningen og kunnskapssektoren. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). KI og risiko for brudd på grunnleggende rettigheter. Fulltekst i vitenarkiv
• Mahler, Tobias (2025). Should All AI Laws be Risk-Based? The Logic and Limits of the AI Act’s Risk-Based Approach. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Design Norms in Law: Just a Passing Fad? doi: https:/cdl.smu.edu.sg/events/research-seminar-prof-lee-andrew-bygrave-design-norms-law-just-passing-fad. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Cognitive Sovereignty in an Era of Obscure Intelligence. doi: https:/bond.edu.au/event/9801/faculty-of-law-twilight-seminar-cognitive-sovereignty-an-era-of-obscure-intelligence. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Design in Law: Rhetoric, Rationale, Reach and Realities. doi: https:/events.unimelb.edu.au/ADMS/event/49619-design-in-law-rhetoric-rationale-reach-and. Fulltekst i vitenarkiv
• Rolfsjord, Sigmund Johannes Ljosvoll; Arnim, Hugh Alexander von; Fatima, Safia & Baselizadeh, Adel (2025). Multimodal Transfer Learning for Privacy in Human Activity Recognition. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). The Utility of Treating "the Mediterranean" as a Regulatory Region. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Fremveksten av EUs cybersikkerhetslovgivning: En fortelling om sitroner, angst, revirkrig, bølger og grå bokser. Fulltekst i vitenarkiv
• Bygrave, Lee Andrew (2025). Sårbarhet i robot-samfunnet. Fulltekst i vitenarkiv
• Lintvedt, Mona Naomi (2025). AI Act. Fulltekst i vitenarkiv
• Nishimura, Markus Yuki; Matsumoto, Kohei & Tørresen, Jim (2026). Diffusion-Based Reinforcement Learning for Multi-Robot Social Navigation. Universitetet i Oslo. Fulltekst i vitenarkiv Vis sammendrag

  --- Abstract and files will be published: 2027-05-15

• Slåttum, Sigmund Kleivene; Høvin, Mats Erling; Wallace, Benedikte & Lindblom, Diana Saplacan (2026). Supervisor for Master thesis: "Moving with the Music: A Novel Robotic Floor for Motion-Enhanced Music Experience" (60 ECTS). University of Oslo (UiO). Fulltekst i vitenarkiv Vis sammendrag

  This thesis investigates how synchronized whole-body movement shapes the experience of listening to music. The two research questions ask whether floor movement changes the listening experience, and whether the specific character of the movement matters for that experience. To address these questions, a one-degree-of-freedom robotic floor was designed and built from scratch. The system, named Harmonic Audio-Reactive Platform (HARP), lifts a person standing on it in a vertical rolling motion derived from features extracted from the music. Two motion patterns were implemented for use in the study: a simple pattern oscillating at the beat frequency, and a complex pattern that combines two sinusoids whose amplitudes vary with the spectral content of the music. The hardware, software, and trajectory generation are described in detail in the thesis, and form a methodological contribution alongside the empirical findings. Six participants took part in a within-group user study. Each experienced three songs from contrasting genres (classical, EDM, and metal) under three motion conditions (no motion, simple, and complex), giving nine conditions per participant. A qualitatively-driven mixed methods design was used. Semi-structured interviews were analyzed with reflexive thematic analysis, alongside Likert ratings, amplitude adjustment logs, synchronization measurements, and video observations. Three themes were constructed from the interviews: Enjoyment, Emotion, and Congruence. Across all data sources, the most consistent finding is that motion pattern preference is personal. No single pattern worked for everyone, and the same pattern could feel mismatched or stressful to one participant and meaningful to another. The movement was mostly received as adding to the listening experience, with Likert ratings, qualitative themes, and participants’ own descriptions of real-world use pointing the same way. Synchronization between music and motion shaped the experience but its specific role could not be settled within this study.

• Bjerkan, Mons Eirik; Watanabe, Shin & Tørresen, Jim (2025). Offline Reinforcement Learning through MPC Bootstrapping. Universitetet i Oslo. Fulltekst i vitenarkiv Vis sammendrag

  Efficient, safe, and robust learning for robotic tasks in the real world is more relevant than ever, with new robots or software improvements emerging rapidly. Accordingly, the popularity of \gls{rl}, and offline \gls{rl} has also massively increased over the last years. There are, however, issues training robots for real-life tasks using \gls{rl} with concerns of safety and the amount of data needed. Offline reinforcement learning is a paradigm with the promise of alleviating some of these challenges. Control algorithms such as \gls{mpc} also aim to solve these complex issues. This approach of using non-learning-based control algorithms has long been the most dominant paradigm within control of complex systems. And has only become more relevant with the emergence of real-time optimization, such as real-time \gls{mpc}. To leverage the best of both worlds, this paper proposes integrating offline \gls{rl} with \gls{mpc} by training an offline \gls{rl} policy solely on pre-collected \gls{mpc} trajectories, thereby effectively bootstrapping the \gls{rl} policy training process. The algorithm aims to avoid excessive exploration for faster convergence towards stronger solutions by leveraging the already provided solutions from the \gls{mpc}, while exploiting the characteristics of \gls{rl} to make up for any weaknesses in the \gls{mpc} solutions to make a robust, safe, and data-efficient solution for task-specific robot training. The proposed method is evaluated in a simulated environment and tested on a quadruped robot navigating through a hilly terrain. Testing shows that the proposed method does not measure up to the performance of pure \gls{mpc}. However, the results indicate that the proposed method can be applied to learn how to solve simpler control tasks.

• Sandanger, Tonje Viddal; Tørresen, Jim; Wiig, Ola; Homlong, Eirik Gromholt & Kumar, Rahul Prasanna (2025). Enhancing Gait Analysis through eXplainable AI. Universitetet i Oslo. Fulltekst i vitenarkiv Vis sammendrag

  Etter kvart som kunstig intelligente (KI) system vert integrert i aukande grad i helsevesenet, er behovet for transparente, pålitelege og klinisk meiningsfulle verktøy viktigare en nokon gang. Denne avhandlinga undersøkjer bruken av maskinlæring og forklarbar KI i klinisk ganganalyse for barn med Celebral Parese (CP). Ved å utnytte rørsle-data frå røynda, utforskar denne studia bruken av djupe-lærings modeller som CNN-LSTM, RNN-LSTM, og ST-GCN, for å sjå korleis desse samanliknast med enklare modellar som RFar. Desse modellane vart trent til å klassifisere Gross Motor Function Classification System (GMFCS) nivå hos barn med CP. Ettersom behovet for pålitelege og forklarbare applikasjonar er avgjerande i helsevesenet, vart SHAP brukt til å lage forklaringer av modellane sine predikasjonar, noko som mogleggjer eit transparent og tolkbart system. Resultata vise at meir komplekse modellar, som ST-GCNane, vart utkonkurrert til fordel for enklare modellar under dataavgrensande forhald, og at dei best ytande modellane vis signifikante resultat for forklaringer med fokus på klinisk relevante funksjonar som korresponderer med det rørte eller kontrarørte beinet. Dette arbeidet framheva óg røynda av nøye modellvalg når ein designar forklarbare KI system, ettersom at SHAP er svært modellavhengig. Det vart derimot funne at når ein brukar ensamble-metodar, vart den totale betydninga av funksjonane fokusert på klinisk relevante plan og ledd, noko som framhev den lovande framtida til forklarbare system. Nokon nye bidrag frå arbeidet er dei tidsmessig justerte SHAP-varmekarta, overlappa gangsyklusen, som mogeleggjer for klinikarar å spore modell- slutningar til spesifikke biomekaniske hendingar. Sjølv om arbeidet bidrar til den aukande integrasjonen av KI-system i helsevesenet, står det att å validere den kliniske nytteverda gjennom direkte tilbakemeldingar frå klinikarar. Framtidig arbeid burde involvere bruker-sentrerte evalueringar, som integrerer domeneekspertar som gir ytterlegare innsikt i tolkbarheiten, relevansen og brukarvenlegheita til forklaringane. Ved å samkøyre denne forskinga med klinisk praksis legg den grunnlaget for bruk av forklarbar KI verktøy i klinisk ganganalyseapplikasjonar, ved å fokusere på openheit og forklarbarheit, samtidig som etiske praksisar vert overheldt.

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