Simultaneous Estimation and Modeling of Robotic Systems with Non-Gaussian State Belief
J. Josiah Steckenrider,J. Josiah Steckenrider
This paper develops a probabilistic simultaneous estimation and modeling (SEAM) framework for estimating a robot’s state and correcting its motion model parameters. This is done by incorporating model uncertainty in state prediction and correcting parameters via optimization. In the proposed technique, belief about a state being estimated is represented by arbitrary multi-dimensional non-Gaussian ...
