Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators
2024
Technical Report
ev
Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper, we propose a novel approach for non-prehensile manipulation which iteratively adapts a physics-based dynamics model for model-predictive control. We adapt the parameters of the model incrementally with a few examples of robot-object interactions. This is achieved by sampling-based optimization of the parameters using a parallelizable rigid-body physics simulation as dynamic world model. In turn, the optimized dynamics model can be used for model-predictive control using efficient sampling-based optimization. We evaluate our few-shot adaptation approach in several object pushing experiments in simulation and with a real robot.
Author(s): | Fabian Baumeister and Lukas Mack and Joerg Stueckler |
Book Title: | CoRR abs/2409.13228 |
Year: | 2024 |
Department(s): | Embodied Vision |
Research Project(s): |
Learning Forward Models for Robotic Manipulation
|
Bibtex Type: | Technical Report (techreport) |
Paper Type: | Technical Report |
Institution: | CoRR |
Note: | Submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025 |
State: | Submitted |
URL: | https://arxiv.org/abs/2409.13228 |
Links: |
preprint
supplemental video |
Video: | |
BibTex @techreport{baumeister2024_mpcsim, title = {Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators}, author = {Baumeister, Fabian and Mack, Lukas and Stueckler, Joerg}, booktitle = {CoRR abs/2409.13228}, institution = {CoRR}, year = {2024}, note = {Submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025}, doi = {}, url = {https://arxiv.org/abs/2409.13228} } |