Incremental few-shot adaptation for non-prehensile object manipulation using parallelizable physics simulators

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 incrementally adapts a physics-based dynamics model for model-predictive control (MPC). The model prediction is aligned with a few examples of robot-object interactions collected with the MPC. This is achieved by using a parallelizable rigid-body physics simulation as dynamic world model and sampling-based optimization of the model parameters. In turn, the optimized dynamics model can be used for MPC using efficient sampling-based optimization. We evaluate our fewshot adaptation approach in object pushing experiments in simulation and with a real robot.

Metadaten
Author:	Fabian Baumeister, Lukas Mack, Joerg Stueckler GND
Frontdoor URL	https://opus.bibliothek.uni-augsburg.de/opus4/127329
ISBN:	979-8-3315-4139-2OPAC
Parent Title (English):	2025 IEEE International Conference on Robotics and Automation (ICRA), 19-23 May 2025, Atlanta, GA, USA
Publisher:	IEEE
Place of publication:	Piscataway, NJ
Editor:	Seth Hutchinson, Nancy Amato, Todd Murphey, Zhidong Wang
Type:	Conference Proceeding
Language:	English
Year of first Publication:	2025
Publishing Institution:	Universität Augsburg
Release Date:	2026/01/13
First Page:	15394
Last Page:	15400
DOI:	https://doi.org/10.1109/icra55743.2025.11128222
Institutes:	Fakultät für Angewandte Informatik
	Fakultät für Angewandte Informatik / Institut für Informatik
	Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Intelligente Perzeption in technischen Systemen
Dewey Decimal Classification:	0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik

Open Access