Manipulation Motion Taxonomy and Coding for Robots
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Abstract (arXiv)
This paper introduces a taxonomy of manipulations as seen especially in cooking for 1) grouping manipulations from the robotics point of view, 2) consolidating aliases and removing ambiguity for motion types, and 3) provide a path to transferring learned manipulations to new unlearned manipulations. Using instructional videos as a reference, we selected a list of common manipulation motions seen in cooking activities grouped into similar motions based on several trajectory and contact attributes. Manipulation codes are then developed based on the taxonomy attributes to represent the manipulation motions. The manipulation taxonomy is then used for comparing motion data in the Daily Interactive Manipulation (DIM) data set to reveal their motion similarities.
Key facts. Cited by 5 papers in the map (data through 13 Oct 2026). First posted on arXiv 1 Oct 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
5 papers.
- 2022Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifoldscited by 10
- 2021Pouring Dynamics Estimation Using Gated Recurrent Unitscited by 1
- 2021Classifying States of Cooking Objects Using Convolutional Neural Networkcited by 0
- 2026ATOM-Bench: A Real-World Benchmark for Atomic Skills and Compositional Generalization in Manipulation Policiescited by 0
- 2026FAN: Foresight Action Normalization for Continual Adaptation of Vision-Language-Action Modelscited by 0
- 2026FAN: Foresight Action Normalization for Continual Adaptation of Vision-Language-Action Models18 Sep 2026
- 2026ATOM-Bench: A Real-World Benchmark for Atomic Skills and Compositional Generalization in Manipulation Policies15 Jun 2026
- 2022Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds4 Oct 2022
- 2021Pouring Dynamics Estimation Using Gated Recurrent Units8 May 2021
- 2021Classifying States of Cooking Objects Using Convolutional Neural Network30 Apr 2021