# Manipulation Motion Taxonomy and Coding for Robots

arXiv: https://arxiv.org/abs/1910.00532 · HTML: https://mlsanity.com/paper/1910.00532/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2019.

## Built on by (most cited first, 5 of 5)

- [Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds](https://mlsanity.com/paper/2210.01672/) (2022)
- [Pouring Dynamics Estimation Using Gated Recurrent Units](https://mlsanity.com/paper/2105.12828/) (2021)
- [ATOM-Bench: A Real-World Benchmark for Atomic Skills and Compositional Generalization in Manipulation Policies](https://mlsanity.com/paper/2606.16826/) (2026)
- [Classifying States of Cooking Objects Using Convolutional Neural Network](https://mlsanity.com/paper/2105.14196/) (2021)
- [FAN: Foresight Action Normalization for Continual Adaptation of Vision-Language-Action Models](https://mlsanity.com/paper/2609.21358/) (2026)

## 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.