Manipulation Motion Taxonomy and Coding for Robots
David Paulius, Yongqiang Huang, Jason Meloncon, Yu Sun

TL;DR
This paper develops a comprehensive taxonomy and coding system for manipulation motions in robotics, especially in cooking, enabling better classification, transfer, and comparison of manipulation skills.
Contribution
It introduces a new taxonomy and coding scheme for manipulation motions, facilitating transfer learning and comparison in robotic manipulation tasks.
Findings
Created a taxonomy of manipulation motions in cooking
Developed a coding scheme based on trajectory and contact attributes
Applied taxonomy to compare motion data in the DIM dataset
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
