movement_primitives: Imitation Learning of Cartesian Motion with Movement Primitives

Abstract :

Movement primitives are a common representation of movements in robotics (Maeda et al., 2017) for imitation learning, reinforcement learning, and black-box optimization of behaviors. There are many types and variations. The Python library movement_primitives focuses on imitation learning (see Figure 1), generalization, and adaptation of movement primitives in Cartesian space. It implements dynamical movement primitives, probabilistic movement primitives, as well as Cartesian and dual Cartesian movement primitives with coupling terms to constrain relative movements in bimanual manipulation. They are implemented in Cython to speed up online execution and batch processing in an offline setting. In addition, the library provides tools for data analysis and movement evaluation.

Links:

https://doi.org/10.21105/joss.06695