The Python LevelSet Toolbox (LevelSetPy)
Not on the map. Why?
Abstract (arXiv)
This paper describes open-source scientific contributions in python surrounding the numerical solutions to hyperbolic Hamilton-Jacobi (HJ) partial differential equations viz., their implicit representation on co-dimension one surfaces; dynamics evolution with levelsets; spatial derivatives; total variation diminishing Runge-Kutta integration schemes; and their applications to the theory of reachable sets. They are increasingly finding applications in multiple research domains such as reinforcement learning, robotics, control engineering and automation. We describe the library components, illustrate usage with an example, and provide comparisons with existing implementations. This GPU-accelerated package allows for easy portability to many modern libraries for the numerical analyses of the HJ equations. We also provide a CPU implementation in python that is significantly faster than existing alternatives.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026Kolmogorov Regression for Robust Diffusion Policiescited by 0
- 2026Kolmogorov Regression for Robust Diffusion Policies16 Jun 2026