go-estimate
A Go library implementing state estimation and filtering algorithms including Kalman, Extended Kalman, Unscented Kalman, and Particle filters.
What is go-estimate?
go-estimate is a Go library that implements state estimation and filtering algorithms for tracking dynamic systems under uncertainty. It provides implementations of Kalman filters, particle filters, and smoothing algorithms to infer system states from noisy measurements. The library solves problems in robotics, navigation, and sensor fusion where accurate real-time state estimation is required.
Go developers and engineers working on robotics, autonomous systems, sensor fusion, navigation, or any application requiring probabilistic state estimation from noisy data.
Developers choose go-estimate for its idiomatic Go implementation of fundamental estimation algorithms, offering a lightweight alternative to larger scientific computing libraries. Its focused suite of filters provides reliability and performance for real-time systems without external dependencies.
Overview
State estimation and filtering algorithms in Go
Use Cases
Best For
- Implementing sensor fusion in autonomous vehicles or drones
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