PyPose v0.6: The Imperative Programming Interface for Robotics
Not on the map. Why?
Abstract (arXiv)
PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has been used in many tasks due to its meticulously designed application programming interface (API) and efficient implementation. From its initial launch in early 2022, PyPose has experienced significant enhancements, incorporating a wide variety of new features into its platform. To satisfy the growing demand for understanding and utilizing the library and reduce the learning curve of new users, we present the fundamental design principle of the imperative programming interface, and showcase the flexible usage of diverse functionalities and modules using an extremely simple Dubins car example. We also demonstrate that the PyPose can be easily used to navigate a real quadruped robot with a few lines of code.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Sep 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 4; 2025: 3.
7 papers.
- 2024MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometrycited by 19
- 2025BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splattingcited by 19
- 2025MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusioncited by 19
- 2024Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomycited by 16
- 2024PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Drivingcited by 7
- 2024Bundle Adjustment in the Eager Modecited by 6
- 2025MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigationcited by 0
- 2025MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusion31 Jul 2025
- 2025MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation27 May 2025
- 2025BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splatting20 Mar 2025
- 2024Bundle Adjustment in the Eager Mode18 Sep 2024
- 2024MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry14 Sep 2024
- 2024Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy23 Jun 2024
- 2024PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving2 Apr 2024