Michel Breyer
Michel Breyer
PhD Student, ETH Zurich
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Cited by
Cited by
Volumetric grasping network: Real-time 6 dof grasp detection in clutter
M Breyer, JJ Chung, L Ott, R Siegwart, J Nieto
Conference on Robot Learning, 1602-1611, 2021
Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
M Breyer, F Furrer, T Novkovic, R Siegwart, J Nieto
IEEE Robotics and Automation Letters, 2019
Object finding in cluttered scenes using interactive perception
T Novkovic, R Pautrat, F Furrer, M Breyer, R Siegwart, J Nieto
2020 IEEE International Conference on Robotics and Automation (ICRA), 8338-8344, 2020
Go fetch: Mobile manipulation in unstructured environments
K Blomqvist, M Breyer, A Cramariuc, J Förster, M Grinvald, F Tschopp, ...
arXiv preprint arXiv:2004.00899, 2020
Dex-net mm: Deep grasping for surface decluttering with a low-precision mobile manipulator
B Staub, AK Tanwani, J Mahler, M Breyer, M Laskey, Y Takaoka, ...
2019 IEEE 15th International Conference on Automation Science and …, 2019
Closed-loop next-best-view planning for target-driven grasping
M Breyer, L Ott, R Siegwart, JJ Chung
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
Learning trajectories for visual-inertial system calibration via model-based heuristic deep reinforcement learning
L Chen, Y Ao, F Tschopp, A Cramariuc, M Breyer, JJ Chung, R Siegwart, ...
Conference on Robot Learning, 1312-1325, 2021
Efficient multi-scale POMDPs for robotic object search and delivery
L Holzherr, J Förster, M Breyer, J Nieto, R Siegwart, JJ Chung
2021 IEEE International Conference on Robotics and Automation (ICRA), 6585-6591, 2021
Unified data collection for visual-inertial calibration via deep reinforcement learning
Y Ao, L Chen, F Tschopp, M Breyer, R Siegwart, A Cramariuc
2022 International Conference on Robotics and Automation (ICRA), 1646-1652, 2022
Efficient Robotic Grasping in Unstructured Environments
M Breyer
ETH Zurich, 2022
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