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Martin Rudorfer

2 accepted papers

2025

RM4D: A Combined Reachability and Inverse Reachability Map for Common 6-/7-Axis Robot Arms by Dimensionality Reduction to 4D

ICRA 2025

Knowledge of a manipulator's workspace is fundamental for a variety of tasks including robot design, grasp planning and robot base placement. Consequently, workspace representations are well studied in robotics. Two important representations are reachability maps and inverse reachability maps. The f

Cited by 5SourceScholar
2022

End-to-End Learning to Grasp via Sampling From Object Point Clouds

RA-L 2022

The ability to grasp objects is an essential skill that enables many robotic manipulation tasks. Recent works have studied point cloud-based methods for object grasping by starting from simulated datasets and have shown promising performance in real-world scenarios. Nevertheless, many of them still

Cited by 35SourcecodeScholar