Division of Robotics, Perception and Learning
The Division of Robotics, Perception and Learning (RPL) performs research in robotics, computer vision and machine learning. Robotic systems that provide advanced service in industry, for search and rescue operations, in medical applications or as assistants to elderly will become an integral part of the future society.
The division is part of the Department of Intelligent Systems at the School of Electrical Engineering and Computer Science.
Research areas
News
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Accepted publications: April22 May 2024
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Accepted publications: May8 Sep 2023
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Accepted publications: March27 Apr 2023
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Accepted publications: February27 Apr 2023
Calendar
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Public defences of doctoral theses
Friday 2025-03-28, 10:54
Location: Kollegiesalen, Brinellvägen 8, Stockholm
Doctoral student: Edvards Scukins , Robotik, perception och lärande, RPL
2025-03-28T10:54:00.000+01:00 2025-03-28T10:54:00.000+01:00 Data-Driven Methods for Enhanced Situation Awareness in Beyond Visual Range Air Combat (Public defences of doctoral theses) Kollegiesalen, Brinellvägen 8, Stockholm (KTH, Stockholm, Sweden)Data-Driven Methods for Enhanced Situation Awareness in Beyond Visual Range Air Combat (Public defences of doctoral theses) -
Public defences of doctoral theses
Monday 2025-03-31, 14:00
Location: F3 (Flodis), Lindstedsvägen 26 & 28, Campus
Video link: https://kth-se.zoom.us/j/66859470351
Doctoral student: Parag Khanna , Robotik, perception och lärande, RPL
2025-03-31T14:00:00.000+02:00 2025-03-31T14:00:00.000+02:00 Adaptive Handovers for Enhanced Human-Robot Collaboration (Public defences of doctoral theses) F3 (Flodis), Lindstedsvägen 26 & 28, Campus (KTH, Stockholm, Sweden)Adaptive Handovers for Enhanced Human-Robot Collaboration (Public defences of doctoral theses) -
Public defences of doctoral theses
Tuesday 2025-04-01, 14:00
Location: F3 (Flodis), Lindstedtsvägen 26
Video link: https://kth-se.zoom.us/j/62755931085
Doctoral student: Simon Holk , Robotik, perception och lärande, RPL
2025-04-01T14:00:00.000+02:00 2025-04-01T14:00:00.000+02:00 Improving Sample-efficiency of Reinforcement Learning from Human Feedback (Public defences of doctoral theses) F3 (Flodis), Lindstedtsvägen 26 (KTH, Stockholm, Sweden)Improving Sample-efficiency of Reinforcement Learning from Human Feedback (Public defences of doctoral theses)