A Factor-Graph-Based Approach to Vehicle Sideslip Angle Estimation

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