44 citations · 66 across the 7 of their papers we have counts for
7 papers
Closed-Loop Next-Best-View Planning for Target-Driven Grasping
Michel Breyer, Lionel Ott, Roland Siegwart +1
Picking a specific object from clutter is an essential component of many manipulation tasks. Partial observations often require the robot to collect additional views of the scene b…
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
Yunke Ao, Le Chen, Florian Tschopp +3
Visual-inertial sensors have a wide range of applications in robotics. However, good performance often requires different sophisticated motion routines to accurately calibrate came…
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
Michel Breyer, Jen Jen Chung, Lionel Ott +2
General robot grasping in clutter requires the ability to synthesize grasps that work for previously unseen objects and that are also robust to physical interactions, such as colli…
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
Le Chen, Yunke Ao, Florian Tschopp +5
Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of…
Go Fetch: Mobile Manipulation in Unstructured Environments
Kenneth Blomqvist, Michel Breyer, Andrei Cramariuc +7
With humankind facing new and increasingly large-scale challenges in the medical and domestic spheres, automation of the service sector carries a tremendous potential for improved…
Object Finding in Cluttered Scenes Using Interactive Perception
Tonci Novkovic, Remi Pautrat, Fadri Furrer +3
Object finding in clutter is a skill that requires perception of the environment and in many cases physical interaction. In robotics, interactive perception defines a set of algori…
Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
Michel Breyer, Fadri Furrer, Tonci Novkovic +2
Enabling autonomous robots to interact in unstructured environments with dynamic objects requires manipulation capabilities that can deal with clutter, changes, and objects' variab…