Motion prediction of moving objects based on autoregressive model
Ashraf Elnagar, Kamal Kant Gupta · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · 1998
In this paper, we describe a framework for predicting future positions and orientation of moving obstacles in a time-varying environment using autoregressive model (ARM) with conditional maximum likelihood estimate of the model parameters. No constraints are placed on the obstacles motion. The proposed algorithm can be used in a variety of applications, one of which is robot motion planning in time varying environments.