# A Factor Graph-based approach to vehicle sideslip angle estimation

arXiv: https://arxiv.org/abs/2107.09815 · HTML: https://mlsanity.com/paper/2107.09815/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 31 references that are in the map.
- First posted on arXiv 21 Jul 2021.

## Builds on (most cited first, 1 of 1)

- [A general framework for modeling and dynamic simulation of multibody systems using factor graphs](https://mlsanity.com/paper/2101.02874/) (2021)

## Abstract (arXiv)

Sideslip angle is an important variable for understanding and monitoring vehicle dynamics but it lacks an inexpensive method for direct measurement. Therefore, it is typically estimated from inertial and other proprioceptive sensors onboard using filtering methods from the family of the Kalman Filter. As a novel alternative, this work proposes modelling the problem directly as a graphical model (factor graph), which can then be optimized using a variety of methods, such as whole dataset batch optimization for offline processing or fixed-lag smoother for on-line operation. Experimental results on real vehicle datasets validate the proposal with a good agreement between estimated and actual sideslip angle, showing similar performance than the state-of-the-art with a great potential for future extensions due to the flexible mathematical framework.