Deere & Company
Probabilistic decision support for obstacle detection and classification in a working area

Abstract:

Systems and methods disclosed herein provide probabilistic decision support regarding detected obstacles in a working area. Real-time data sets are collected from obstacle sensors associated with at least one self-propelled work vehicle, corresponding to detected presence/absence of obstacles at given locations within the working area. The received real-time data sets are integrated in data storage comprising a priori data sets corresponding to the working area, to generate one or more new a priori data sets. Probabilities are determined for the detected presence or absence of the obstacle, and for each of one or more obstacle categories, based on the received real-time data set and at least an a priori data set corresponding to the work vehicle's location. An output corresponding to at least a most likely of the determined probabilities is generated as feedback to a user interface, and/or relevant machine control units.