at Google ScholarTitle data
Hartwig, Johannes ; Kögler, Marcello ; Henrich, Dominik:
Neural Network-Based In-Contact Task Segmentation of Demonstrated Robot Motions via Hand Guiding.
2025
Event: 1st German Robotics Conference
, 13.-15. March 2025
, Nuremberg.
(Conference item: Conference
,
Paper
)
Abstract in another language
Intuitive robot programming approaches, such as Programming by Demonstration, enable non-experts to teach robots tasks through hand-guided demonstrations. However, for in-contact tasks requiring force control for parts of the motion, automated segmentation of motion types is crucial for improving usability. Considering the related work, this work proposes a neural network-based segmentation method categorizing motion into three fundamental types using input data of cartesian twists and wrenches at the end effector. We collect demonstration data using a 7-axis robot with a wrist-mounted force torque sensor and generate ground truth labeling by hand. While still in development, our research direction aims to enable non-experts to program in-contact tasks more intuitively.
Further data
| Item Type: | Conference item (Paper) |
|---|---|
| Refereed: | No |
| Additional notes: | Accepted for publication at 1st German Robotics Conference (to appear) |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III > Chair Applied Computer Science III - Univ.-Prof. Dr. Dominik Henrich |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 22 Jul 2025 07:03 |
| Last Modified: | 22 Jul 2025 07:03 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/94264 |