Manipulation Motion Taxonomy and Coding for Robots
This work addresses the need for clear motion definitions and transfer learning in robotics, but it is incremental as it builds on existing datasets and focuses on a specific domain.
The paper tackles the problem of standardizing robot manipulation motions in cooking by introducing a taxonomy and coding system based on trajectory and contact attributes from instructional videos, and applies it to analyze motion similarities in the Daily Interactive Manipulation dataset.
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.