Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Identifying physical interactions between a robot and its environment can improve autonomous robot manipulation. Methods in the literature can identify meaningful physical interactions, such as constraints, from a single task demonstration. However, they do not scale well when a wide variety of different physical interactions may be encountered. To alleviate this limitation, this work proposes to model physical interactions with interaction frames: reference frames that attach to the robot and/or ground body and have interaction classes associated with each axis. Interaction frames are identified by minimizing and decoupling the Cartesian mechanical power components in demonstration data. Thereby, interaction frames identify what interactions take place where , for example at geometric features. The method is evaluated in three experiments. First, identification accuracy is evaluated through several single‐constraint experiments comparing velocity‐based, force‐based, and the proposed power‐based method, where the latter is found to be advantageous. Second, the method is applied to a task demonstration that contains different sequential contacts. Third, it is illustrated how the method can be used as a basis for Learning from Demonstration, by reproducing the sequential task from a single demonstration. The method can be applied with little prior information, to advance the development of versatile robots.

Authors

Institutions

Publication Details

Journal
Advanced Robotics Research
Published
2025-09-25
DOI
https://doi.org/10.1002/adrr.202500109
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Douwe Dresscher, Mark Vlutters, Herman van der Kooij, Alex Harm Gert‐Jan Overbeek
1 citations
Advanced Robotics Research
Robot Manipulation and Learning
1.21
article

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Douwe Dresscher, Mark Vlutters, Herman van der Kooij, Alex Harm Gert‐Jan Overbeek
article en
1 citations

Abstract

Identifying physical interactions between a robot and its environment can improve autonomous robot manipulation. Methods in the literature can identify meaningful physical interactions, such as constraints, from a single task demonstration. However, they do not scale well when a wide variety of different physical interactions may be encountered. To alleviate this limitation, this work proposes to model physical interactions with interaction frames: reference frames that attach to the robot and/or ground body and have interaction classes associated with each axis. Interaction frames are identified by minimizing and decoupling the Cartesian mechanical power components in demonstration data. Thereby, interaction frames identify what interactions take place where , for example at geometric features. The method is evaluated in three experiments. First, identification accuracy is evaluated through several single‐constraint experiments comparing velocity‐based, force‐based, and the proposed power‐based method, where the latter is found to be advantageous. Second, the method is applied to a task demonstration that contains different sequential contacts. Third, it is illustrated how the method can be used as a basis for Learning from Demonstration, by reproducing the sequential task from a single demonstration. The method can be applied with little prior information, to advance the development of versatile robots.

Advanced Robotics Research
University of Twente (NL)
Openalex Percentile: Top 16%
Robot Manipulation and Learning
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration — Douwe Dresscher, Mark Vlutters, et al. · Advanced Robotics Research (2025) | TGRS Research Map | TGRS