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Mårten Björkman
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Year
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
1632006
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
146*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
1452010
Enhancing visual perception of shape through tactile glances
M Bjorkman, Y Bekiroglu, V Hogman, D Kragic
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International …, 2013
1442013
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
1312005
Active 3D scene segmentation and detection of unknown objects
M Björkman, D Kragic
2010 IEEE international conference on robotics and automation, 3114-3120, 2010
1032010
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
672020
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
652014
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
582004
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
552016
Deep reinforcement learning to acquire navigation skills for wheel-legged robots in complex environments. In 2018 IEEE
X Chen, A Ghadirzadeh, J Folkesson, M Björkman, P Jensfelt
RSJ International Conference on Intelligent Robots and Systems (IROS), 3110-3116, 2018
53*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
512010
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
502019
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
482002
An attentional system combining top-down and bottom-up influences
B Rasolzadeh, M Björkman, JO Eklundh
International Cognitive Vision Workshop (ICVW06), 2006
442006
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
402011
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
382006
Combining planning and learning of behavior trees for robotic assembly
J Styrud, M Iovino, M Norrlöf, M Björkman, C Smith
2022 International Conference on Robotics and Automation (ICRA), 11511-11517, 2022
352022
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
342020
Scene understanding through autonomous interactive perception
N Bergström, CH Ek, M Björkman, D Kragic
Computer Vision Systems: 8th International Conference, ICVS 2011, Sophia …, 2011
292011
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Articles 1–20