patterns received from fleet management and 4 the self learned patterns original patterns may be comprised of the pre defined patterns i e labeled training data implemented by the control designer in an offline way e g generic patterns as shown in fig1 2 and 3 updated patterns may be comprised of improvements on the original patterns based on existing or newly installed sensor measurements on the vehicle e g weight of the load or distances taken on the route learned during vehicle operation or operator operation received patterns may be comprised of information received by a fleet management server and or cloud i e information from other vehicles or infrastructure through a communication system installed on the vehicle for example an operation of a forklift such as lifting a pallet from a truck in the warehouse entrance and storing it in a rack at a particular location can form a new label for the sequences of tasks and can be shared with all other vehicles of the fleet as other vehicles learn the new pattern for the first time they can properly operate the same sequence of tasks in replacement with the first vehicle by immediately recognizing the new pattern self learned patterns may be comprised of patterns not included in the originally installed patterns the recognition algorithm can detect and record repetitive movements by the vehicle or the operator a separate space on the vehicle memory is allocated to store all the new patterns followed by the vehicle progressively the controller will interpret this sequence of actions by clustering methods and these actions can form new labels by.