Intelligent Systems
Note: This research group has relocated.

Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators

2024

Technical Report

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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}
}