Michel Breyer

According to our database, Michel Breyer authored at least 11 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Efficient Robotic Grasping in Unstructured Environments.

Michel Breyer

PhD thesis, 2022

Closed-Loop Next-Best-View Planning for Target-Driven Grasping.

Michel Breyer, Lionel Ott, Roland Siegwart, Jen Jen Chung

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning.

Yunke Ao, Le Chen, Florian Tschopp, Michel Breyer, Roland Siegwart, Andrei Cramariuc

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

Efficient Multi-scale POMDPs for Robotic Object Search and Delivery.

Luc Holzherr, Julian Förster, Michel Breyer, Juan I. Nieto, Roland Siegwart, Jen Jen Chung

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

Go Fetch: Mobile Manipulation in Unstructured Environments.

Kenneth Blomqvist, Michel Breyer, Andrei Cramariuc, Julian Förster, Margarita Grinvald, Florian Tschopp, Jen Jen Chung, Lionel Ott, Juan I. Nieto, Roland Siegwart

CoRR, 2020

Object Finding in Cluttered Scenes Using Interactive Perception.

Tonci Novkovic, Rémi Pautrat, Fadri Furrer, Michel Breyer, Roland Siegwart, Juan I. Nieto

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning.

Le Chen, Yunke Ao, Florian Tschopp, Andrei Cramariuc, Michel Breyer, Jen Jen Chung, Roland Siegwart, César Cadena

Proceedings of the 4th Conference on Robot Learning, 2020

Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter.

Michel Breyer, Jen Jen Chung, Lionel Ott, Roland Siegwart, Juan I. Nieto

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning.

Michel Breyer, Fadri Furrer, Tonci Novkovic, Roland Siegwart, Juan I. Nieto

IEEE Robotics Autom. Lett., 2019

Dex-Net MM: Deep Grasping for Surface Decluttering with a Low-Precision Mobile Manipulator.

Benno Staub, Ajay Kumar Tanwani, Jeffrey Mahler, Michel Breyer, Michael Laskey, Yutaka Takaoka, Max Bajracharya, Roland Siegwart, Ken Goldberg

Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018

Flexible Robotic Grasping with Sim-to-Real Transfer based Reinforcement Learning.

Michel Breyer, Fadri Furrer, Tonci Novkovic, Roland Siegwart, Juan I. Nieto

CoRR, 2018