The goal of the lab is to develop methods and techniques to extract meaningful information from sensor data where such data emerges from complex physical systems such as robots and/or sensor networks. The extraction of this information is to facilitate good interaction between humans and systems, as well as between systems. Our investigations aim to provide semantically rich representations of data using AI techniques within machine learning and automated reasoning. We further study the impact of our methods by studying the quality of interaction it provides with humans and other agents. Our research is situated in a number of different topics and fields where we work together with industry and other academic partners, and include social robotics, smart home environments, multi-agent systems and more.
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Recent Posts
- Keynote at ECAI 2020 2020-10-08
- STAIRS paper accepted at ECAI 2020 2020-08-26
- IEEE Transactions on Control System Technology —– paper accepted 2020-08-19
- RO-MAN 2020 – Paper accepted 2020-06-29
- QISAR Workshop 2020 2020-05-12
- IJCAI 2020 – Demo Paper Accepted 2020-05-02
- IJCAI 2019 Distinguished Paper Nomination / Visual Intelligence for Autonomous Driving 2019-08-14
- Keynote by Prof. Mehul Bhatt / Workshop @ IEEE RO-MAN 2019 2019-08-05
- IJCAI 2019 / Autonomous Driving 2019-06-24
- Cognitive Vision 2019 2019-04-15