A framework for vision based bearing only 3D SLAM P Jensfelt, D Kragic, J Folkesson, M Bjorkman Proceedings 2006 IEEE International Conference on Robotics and Automation …, 2006 | 163 | 2006 |
Deep predictive policy training using reinforcement learning A Ghadirzadeh, A Maki, D Kragic, M Björkman 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 145* | 2017 |
An active vision system for detecting, fixating and manipulating objects in the real world B Rasolzadeh, M Björkman, K Huebner, D Kragic The International Journal of Robotics Research 29 (2-3), 133-154, 2010 | 141 | 2010 |
Enhancing visual perception of shape through tactile glances M Björkman, Y Bekiroglu, V Högman, D Kragic 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 139 | 2013 |
Vision for robotic object manipulation in domestic settings D Kragic, M Björkman, HI Christensen, JO Eklundh Robotics and autonomous Systems 52 (1), 85-100, 2005 | 127 | 2005 |
Active 3D scene segmentation and detection of unknown objects M Björkman, D Kragic 2010 IEEE international conference on robotics and automation, 3114-3120, 2010 | 102 | 2010 |
Detecting, segmenting and tracking unknown objects using multi-label MRF inference M Björkman, N Bergström, D Kragic Computer Vision and Image Understanding 118, 111-127, 2014 | 65 | 2014 |
Human-centered collaborative robots with deep reinforcement learning A Ghadirzadeh, X Chen, W Yin, Z Yi, M Björkman, D Kragic IEEE Robotics and Automation Letters 6 (2), 566-571, 2020 | 57 | 2020 |
Combination of foveal and peripheral vision for object recognition and pose estimation M Bjorkman, D Kragic IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 57 | 2004 |
A sensorimotor reinforcement learning framework for physical human-robot interaction A Ghadirzadeh, J Bütepage, A Maki, D Kragic, M Björkman 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 54 | 2016 |
Deep reinforcement learning to acquire navigation skills for wheel-legged robots in complex environments X Chen, A Ghadirzadeh, J Folkesson, M Björkman, P Jensfelt 2018 IEEE/RSJ international conference on intelligent robots and systems …, 2018 | 52 | 2018 |
Attention-based active 3D point cloud segmentation M Johnson-Roberson, J Bohg, M Björkman, D Kragic 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010 | 51 | 2010 |
Real-time epipolar geometry estimation of binocular stereo heads M Bjorkman, JO Eklundh IEEE Transactions on pattern analysis and machine intelligence 24 (3), 425-432, 2002 | 48 | 2002 |
An attentional system combining top-down and bottom-up influences B Rasolzadeh, A Tavakoli Targhi, JO Eklundh Attention in Cognitive Systems. Theories and Systems from an …, 2007 | 42 | 2007 |
Generating object hypotheses in natural scenes through human-robot interaction N Bergström, M Björkman, D Kragic 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 39 | 2011 |
Vision in the real world: Finding, attending and recognizing objects M Björkman, JO Eklundh International Journal of Imaging Systems and Technology 16 (5), 189-208, 2006 | 38 | 2006 |
Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration GZ Gandler, CH Ek, M Björkman, R Stolkin, Y Bekiroglu Robotics and Autonomous Systems 126, 103433, 2020 | 34 | 2020 |
Meta-learning for multi-objective reinforcement learning X Chen, A Ghadirzadeh, M Björkman, P Jensfelt 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 33 | 2019 |
Scene understanding through autonomous interactive perception N Bergström, CH Ek, M Björkman, D Kragic Computer Vision Systems: 8th International Conference, ICVS 2011, Sophia …, 2011 | 29 | 2011 |
Strategies for multi-modal scene exploration J Bohg, M Johnson-Roberson, M Björkman, D Kragic 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010 | 28 | 2010 |