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PIRC - Predictive and Intuitive Robot Companion

PIRC targets a psychology-inspired computing breakthrough through research combining insight from cognitive psychology with computational intelligence to build models that forecast future events and respond dynamically.

Robot assistant

1113194150 © Miriam Doerr Martin Frommherz | shutterstock.com

About the project

The systems will be aware and alert for how to best act given their knowledge about themselves and perception of their environment. Humans anticipate future events more effectively than computers. We combine sensing across multiple modalities with learned knowledge to predict outcomes and choose the best actions. Can we transfer these skills to intelligent systems in human-interactive scenarios?

Artificial intelligence meets cognitive neuropsychology

In PIRC, we will apply our machine learning and robotics expertise, and collaborate with researchers in cognitive psychology. The goal is to apply recent models of human prediction and intuitive action on perception-action loops of future intelligent robot companions.

Our work will allow such robots to adapt and act more seamlessly with their environment than the current technology. We will equip the robots with these new skills and in addition, provide them with the knowledge that users they are interacting with, apply the same mechanisms. This will include mechanisms for adaptive response time from quick and intuitive to slower and well-reasoned. The models will be applied in two robotics applications with potential for very wide impact: physical rehabilitation and home care robot support for older people.

See more information and ROBIN student master projects here.

Publications

  • Nergård, Katrine Linnea; Endestad, Tor & Tørresen, Jim (2022). Effect of Hand Dominance When Decoding Motor Imagery Grasping Tasks. In Ribei, Paulo Rogério de Almeida; Cota, Vinícius Rosa; Barone, Dante Augusto Couto & de Oliveira, Alexandre César Muniz (Ed.), Computational Neuroscience: Conference Proceedings Third Latin American Workshop, LAWCN 2021, São Luís, Brazil, December 8–10, 2021, Revised Selected Papers. Springer Nature. ISSN 978-3-031-08443-0. p. 233–249. doi: https%3A/doi.org/10.1007/978-3-031-08443-0_15.
  • van Otterdijk, Marieke; Song, Heqiu; Tsiakas, Konstantinos; van Zeijl, Ilka & Barakova, Emilia (2022). Nonverbal Cues Expressing Robot Personality - A Movement Analysts Perspective. In Orlandini, Andrea; Recchiuto, Carmine & Rossi, Silvia (Ed.), Proceedings of the 31st IEEE International Conference on Robot & Human Interactive Communication - RO-MAN. IEEE conference proceedings. ISSN 978-1-6654-0680-2. doi: 10.1109/RO-MAN53752.2022.9900647.
  • Tørresen, Jim & Nakazawa, Atsushi (2022). Ethical Considerations in User Modeling and Personalization (ECUMAP). In Bellogin, Alejandro; Boratto, Ludovico; Santos, Olga C.; Ardissono, Liliana & Knijnenburg, Bart (Ed.), UMAP'22: Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM). ISSN 978-1-4503-9207-5. p. 351–353.
  • Saplacan, Diana & Tørresen, Jim (2022). Robots as Welfare Technologies to Reduce Falls Amongst Older Adults: An Explorative Study from Norway, Human Aspects of IT for the Aged Population. Technology in Everyday Living. Lecture Notes in Computer Science. LNCS 13331. Springer Nature Switzerland AG. ISSN 978-3-031-05654-3. p. 88–106.
  • Hou, Jie; Bordvik, David; Noori, Farzan Majeed; Uddin, Md Zia & Tørresen, Jim (2022). Monitoring In-Home Emergency Situation and Preserve Privacy using Multi-modal Sensing and Deep Learning, 2022 International Conference on Electronics, Information, and Communication (ICEIC 2022) . IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665409353. doi: 10.1109/ICEIC54506.2022.9748829.
  • Baselizadeh, Adel; Khaksar, Weria & Tørresen, Jim (2022). Motion Planning and Obstacle Avoidance for Robot Manipulators Using Model Predictive Control-based Reinforcement Learning. In Filev, Dimitar; Zhou, MengChu & Tunsel, Edward (Ed.), 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-6654-5257-1. p. 1584–1591. doi: 10.1109/SMC53654.2022.9945504.
  • Gorton, Patrick & Ellefsen, Kai Olav (2021). Evaluating Predictive Deep Learning Models. In Yildirim Yayilgan, Sule; Bajwa, Imran Sarwar & Sanfilippo, Filippo (Ed.), Proceeding of the 3rd International Conference on Intelligent Technologies and Applications (INTAP). Springer. ISSN 978-3-030-71711-7. p. 139–150. doi: doi.org/10.1007/978-3-030-71711-7_12. Full text in Research Archive
  • Noori, Farzan Majeed; Uddin, Md Zia & Tørresen, Jim (2021). Ultra-Wideband Radar-Based Activity Recognition Using Deep Learning. IEEE Access. ISSN 2169-3536. 9, p. 138132–138143. doi: 10.1109/ACCESS.2021.3117667. Full text in Research Archive
  • van Otterdijk, Marieke; Neggers, Margot; Tørresen, Jim & Barakova, Emilia Ivanova (2021). Preferences of Seniors for Robots Delivering a Message With Congruent Approaching Behavior, Proceedings of the 2021 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO) Virtual Conference, July 8-10, 2021. IEEE Robotics and Automation Society. ISSN 978-1-6654-4952-6. doi: 10.1109/ARSO51874.2021.9542833.
  • Baselizadeh, Adel; Saplacan, Diana & Tørresen, Jim (2021). Adaptive Real-time Learning-based Neuro-Fuzzy Control of Robot Manipulators. In Plapper, Peter (Eds.), 9th International Conference on Control, Mechatronics and Automation (ICCMA2021). IEEE conference proceedings. ISSN 978-1-6654-10731. p. 20–26. doi: 10.1109/ICCMA54375.2021.9646224.

View all works in Cristin

  • Saplacan, Diana (2022). AI & Ethics Workshop.
  • Saplacan, Diana (2022). Participatory Design and Human-Robot Interaction - An ethical and inclusive perspective on contemporary technologies.
  • Saplacan, Diana (2022). Healthcare Professionals’ Attitudes towards the Organization of Care Services and the Adoption of Welfare Robots in Norway.
  • Dahl, Heidi Elisabeth Iuell; Mehmandarov, Rustam Karim; Harkestad, Inge & Saplacan, Diana (2022). AI and Ethics workshop.
  • Saplacan, Diana (2022). Robots as Welfare Technologies to Reduce Falls Amongst Older Adults: An Explorative Study from Norway.
  • Saplacan, Diana (2022). Tutorial presentation. Title: "Robots and Society: Challenges and Opportunities within social Human-Robot Interaction" at 31st IEEE International Conference on Robot & Human Interactive Communication.
  • Saplacan, Diana (2022). What do we talk about when we talk about social robots vs. robot sociomorphism ? Empirical examples from previous and ongoing research.
  • Ellefsen, Kai Olav (2022). Towards more Human Robot Brains.
  • van Otterdijk, Marieke; Song, Heqiu; Tsiakas, Konstantinos; van Zeijl, Ilka & Barakova, Emilia (2022). Nonverbal Cues Expressing Robot Personality - a Movement Analysts Perspective.
  • van Otterdijk, Marieke; Saplacan, Diana; Laeng, Bruno & Torresen, Jim (2022). Explorative Study on Human Intuitive Responses to Observing Expressive Robot Behavior.
  • Saplacan, Diana (2022). Ethics: Autonomous Technologies for All (ATA)?
  • Saplacan, Diana (2022). Guest Lecture: Ongoing research with Social and Assistive Robots: Research projects, empirical examples, and theory.
  • Saplacan, Diana (2022). TIAGo wishes you welcome to a debate on the theme: Should a robot be involved in care tasks? (Norwegian title: TIAGo ønsker velkommen til en debatt med tema: Bør en robot involveres i omsorgsoppgaver?).
  • Saplacan, Diana; Baselizadeh, Adel & Tørresen, Jim (2022). Robot Demonstration: Meet TIAGo the robot! The robot showcases several tasks: brushing hair, putting the lipstick on, using a (plastic) knife, moving an object, carrying a bag.
  • Reilstad, Didrik Spanne; Strand, Ørjan; Wu, Zhenying; Castro da Silva, Bruno; Torresen, Jim & Ellefsen, Kai Olav (2022). RADAR: Reactive and Deliberative Adaptive Reasoning – Learning When to Think Fast and When to Think Slow.
  • Saplacan, Diana (2022). Ethical Issues in Mobile Robots - Guest Lecture for Norwegian University of Life Sciences (NMBU), at the Faculty of Science and Technology, part of Human-Robot Interaction Course, Advanced Topics in Mobile robots.
  • Sumioka, Hidenobu; Tørresen, Jim; Shiomi, Masahiro; Chen, Liang-Kung & Nakazawa, Atsushi (2022). Editorial: Interaction in robot-assistive elderly care. Frontiers in Robotics and AI. ISSN 2296-9144. 9. doi: 10.3389/frobt.2022.1020103.
  • Tørresen, Jim (2022). Introduction to Research Visit to University of Oslo in Norway.
  • Saplacan, Diana (2022). Ongoing research with Social and Assistive Robots - Presentation for the National Commitee in Research Ethics in Science and Technology (NENT).
  • Tørresen, Jim; Atsushi, Nazawa; Saplacan, Diana; Prestes, Edson; Mahler, Tobias & Weng, Yueh-Hsuan (2022). Tutorial at IROS 2022 - Ethical, Legal and User Perspectives on Robots and Systems (ELAUPORAS) – Assessments and Potential Measures.
  • Tørresen, Jim (2022). Research on health-related treatment and care technology – A technical and ethical view.
  • Tørresen, Jim (2022). Tutorial: Ethical challenges for Autonomous and Multiagent Systems.
  • Tørresen, Jim (2022). Keynote: Multi-Modal Sensing for Care Robots for Older People.
  • Tørresen, Jim (2022). Sensing, acting and adapting in the real world.
  • Tørresen, Jim & Nakasawa, Atsushi (2022). Tutorial: Ethical Considerations in User Modeling and Personalization (ECUMAP).
  • Tørresen, Jim (2022). Tutorial: Ethical Challenges in Computational Intelligence Research.
  • Tørresen, Jim (2022). Ethical Perspectives of Robotics and AI – How to develop preferable system? .
  • Tørresen, Jim (2022). Introduction to Research Visit to University of Oslo in Norway.
  • Saplacan, Diana; Tørresen, Jim; Weng, Yueh-Hsuan & Li, Phoebe (2022). Tutorial: Robots and Society (RO-SO 2022) / Ethical perspectives and technical challenges and opportunities with care robots.
  • Tørresen, Jim (2021). How to achieve ethical artificial intelligence (AI) research and development?
  • Saplacan, Diana (2021). Ethics and Technology.
  • Saplacan, Diana; Tørresen, Jim; Mahler, Tobias & Fosch-Villaronga, Eduard (2021). Robots and Society: Ethical, Legal, and Technical Perspectives on Integrating Robots in the Home- and Healthcare Systems and Services (RO-SO).
  • Tørresen, Jim (2021). Tutorial: Ethical Considerations in User Modeling and Personalization.
  • Tørresen, Jim (2021). Kunstig intelligens – allsidig i metoder og anvendelser.
  • Tørresen, Jim (2021). Tutorial: Explainability, Trust and Ethics for Robots and Autonomous Systems.
  • Tørresen, Jim (2021). Tutorial: Intelligent System Research – AI Ethical Challenges and Opportunities.
  • Tørresen, Jim (2021). INTROMAT: INtroducing personalized TReatment Of Mental health problems using Adaptive Technology.
  • Tørresen, Jim (2021). Tutorial: Ethical Considerations in Robotics and Automation.
  • Tørresen, Jim; Saplacan, Diana; Lintvedt, Mona Naomi; Mahler, Tobias & Fosch-Villaronga, Eduard (2021). Tutorial: Ethical and Legal Assessments Related to Robots and Systems .
  • Tørresen, Jim (2021). Introducing a Multimodal Elderly Care Safety Alarm Robot.
  • Tørresen, Jim (2021). Tutorial: Ethical Considerations in the Development and Use of Neural Information Processing Systems.
  • Tørresen, Jim; Pettersen, Klas Henning & Goodwin, Morten (2021). NORA forklarer kunstig intelligens – Podcast #6 med Jim Tørresen . [Internet]. Podcast.
  • Tørresen, Jim (2020). Tutorial: Ethical Challenges and Opportunities within Computational Intelligence System Development.
  • Ellefsen, Kai Olav (2020). Hva kan intelligente maskiner lære av biologisk liv? Biolog. ISSN 0801-0722. p. 16–19.
  • Tørresen, Jim (2020). Ethical Consideration in Robotics and Intelligent Systems Research.
  • Gorton, Patrick Ribu & Ellefsen, Kai Olav (2020). Evaluating Predictive Deep Learning Models.
  • Ellefsen, Kai Olav & Time, Jon Kåre (2020). Han lærer roboter hvordan verden fungerer. [Newspaper]. https://morgenbladet.no/aktuelt/2020/02/han-laerer-roboter-h.
  • Soma, Rebekka; Saplacan, Diana & Sikora, Magdalena Claudia (2022). Exploring personality and behavior with a robot table - a qualitative case study. Reprosentralen, University of Oslo.
  • Roa Gran, Kristian & Ellefsen, Kai Olav (2022). Learning to drive by predicting the future: Direct Future Prediction. Universitetet i Oslo.
  • Bordvik, David Andreas; Ellefsen, Kai Olav & Riemer-Sørensen, Signe (2022). Forecasting regulation market balancing volumes from market data and weather data using Deep Learning and Transfer Learning. Universitetet i Oslo.
  • Thoresen, Sindre & Ellefsen, Kai Olav (2021). Solving Long Term Planning Problems with Direct Future Prediction. Universitetet i Oslo.
  • Ellefsen, Kai Olav & Bjørsvik, Vegard (2021). Solving Sparse Reward Environments Using Go-Explore with Learned Cell Representation. Universitetet i Oslo.
  • Sørensen, Scott Andreas Fiskerstrand & Ellefsen, Kai Olav (2020). Comparing Model-Free and Model-Based Reinforcement Learning for Collision Avoidance. Universitetet i Oslo.
  • Gorton, Patrick & Ellefsen, Kai Olav (2020). Backpropagating to the Future: Evaluating Predictive Deep Learning Models. Universitetet i Oslo.

View all works in Cristin

Tags: robotics, artificial intelligence, robot assistance, rehabilitation
Published Oct. 11, 2020 7:17 AM - Last modified Mar. 2, 2022 1:49 PM