Crown Equipment Corporation

Jacob Jay Thomson

Lucas B Waltz

Lisa Wong

Kashyap Chandrasekar

Ryan Michaels Estep

Lucas Waltz

Mark Bell

Timothy William Fanselow

Timothy Fanselow

A process to schedule an industrial vehicle for maintenance comprises constructing a warehouse model based upon a warehouse configuration to define a dimensionally constrained environment and virtual industrial vehicles operating within the environment. A workflow model defines tasks of the virtual industrial vehicles within the defined environment of the warehouse model. A kinematic model is based upon vehicle specifications for the virtual industrial vehicles, kinematic functions of the virtual industrial vehicles, constraints of the defined environment of the warehouse model, and a cutback curve computed for a parameter of a kinematic function of the virtual industrial vehicle. The kinematic model is applied to the workflow model to evaluate virtual industrial vehicle performance to determine ideal results. Actual use data of the industrial vehicle is collected during the industrial vehicle operation. The industrial vehicle is scheduled for maintenance based on a comparison of the actual use data to the ideal results.

Industrial vehicle fleet recommender

A process for recommending a fleet of industrial vehicles comprises receiving, via a user interface, input variables concerning a warehouse configuration and operational variables concerning a fleet configuration. Instances of a warehouse model, an operations model, vehicle specifications, and workflow parameters are created where the workflow parameters are established workflow models derived from the warehouse configuration and vehicle specifications. A workflow model is simulated using kinematic models of the vehicles by defining a workflow model defining tasks of the industrial vehicles within an environment associated with performance of an operation, wherein the workflow model is based on the workflow parameters and associating the tasks with the kinematic models, which incorporate cutback curves. The kinematic model is applied to the workflow model based upon travel paths of the workflow model to determine results. A recommendation for vehicles of a vehicle type based on the simulation results is recommended.

A process for modifying vehicle performance parameters for one or more kinematic functions while executing an assigned task is disclosed. The process comprises receiving, for an industrial vehicle, a job specification and decomposing the job specification into a workflow model, with the workflow model defining the tasks of the industrial vehicle. The process further comprises associating the tasks with a kinematic model. The kinematic model is generated by identifying the kinematic function of the industrial vehicle, receiving constraints associated with an operation of the industrial vehicle, and computing a cutback curve for a parameter of the kinematic function. The kinematic model is applied to the workflow model. The performance parameter of the industrial vehicle is modified based on the applied kinematic model to the workflow model.

Adjusting industrial vehicle performance

A method for vehicle positioning or navigation utilizing associated feature pairs may include creating a plurality of associated feature pairs by retrieving an initial set of camera data from the camera comprising two-dimensional UV space information, forming pairs from the UV space information, and associating each pair from the UV space information with pairs from each of the plurality of three-dimensional global feature points of the industrial facility map, calculating a best estimate poses from calculated vehicle poses of the associated feature pairs, using an accumulated odometry to update the best estimate pose to a current localized position and setting a seed position as the current localized position. The navigation of the materials handling vehicle is tracked and/or navigated along the inventory transit surface navigate in at least a partially automated manner utilizing the current localized position.

Vehicle positioning or navigation utilizing associated feature pairs

Systems and methods for calibrating an image capture device for a materials handling vehicle. One embodiment of a system includes the image capture device and a vehicle computing device, where the vehicle computing device stores logic that when executed by a processor, causes the materials handling vehicle to determine a current location of the materials handling vehicle in a warehouse and determine a seed value associated with the image capture device, the seed value representing initial calibration parameters of the image capture device. In some embodiments, the logic causes the materials handling vehicle to capture image data in the warehouse, compare the image data with a site map, and determine a calibrated value for the image capture device from the comparison and the seed value.

Systems and methods for image capture device calibration for a materials handling vehicle

A computer-executed process and system for evaluating industrial vehicle performance comprises identifying kinematic functions of an industrial vehicle, receiving constraints of an environment in which the industrial vehicle operates, and computing a cutback curve for a parameter of a select kinematic function of the industrial vehicle. A kinematic model of the industrial vehicle is generated based on the kinematic functions, the constraints of the environment, and the cutback curves. A workflow model is defined by defining tasks of the industrial vehicle within the environment, wherein the tasks are based upon the kinematic model. The kinematic model and workflow model is used to simulate a job specification, and the results of the simulation are used to evaluate an industrial vehicle.

According to the embodiments described herein, a method for vehicle positioning or navigation utilizing associated feature pairs may include creating a plurality of associated feature pairs by retrieving an initial set of camera data from the camera comprising two-dimensional UV space information, forming pairs from the UV space information, and associating each pair from the UV space information with pairs from each of the plurality of three-dimensional global feature points of the industrial facility map, calculating a best estimate poses from calculated vehicle poses of the associated feature pairs, using an accumulated odometry to update the best estimate pose to a current localized position and setting a seed position as the current localized position. The navigation of the materials handling vehicle is tracked and/or navigated along the inventory transit surface navigate in at least a partially automated manner utilizing the current localized position.

A method for coordinating path planning for one or more automated vehicles is described, including querying an online path planner for possible solutions for at least one executable task for each of the one or more automated vehicles, examining the results of the query, deciding a coordinated path plan for each vehicle, and communicating the coordinated path plan to a traffic manager, wherein the traffic manager ensures that the one or more automated vehicles perform each executable task according to the coordinated path plan.

System for efficient scheduling for multiple automated non-holonomic vehicles using a coordinated path planner

According to the embodiments described herein, a method for environmental based localization may include capturing an input image of a ceiling comprising a plurality of skylights. Features can be extracted from the input image. The features can be grouped into a plurality of feature groups such that each of the feature groups is associated with one of the skylights. Line segments can be extracted from the features of each feature group, automatically, with one or more processors executing a feature extraction algorithm on each feature group separately. At least two selected lines of the line segments of each feature groups can be selected. A centerline for each of the feature groups can be determined based at least in part upon the two selected lines. The center line of each of the feature groups can be associated with one of the skylights.

Industrial vehicles with overhead light based localization

According to the embodiments described herein, an industrial vehicle can include an Environmental Based Localization (EBL) sensor communicatively coupled to one or more processors. The EBL sensor can detect objects within a field of view. The one or more processors execute machine readable instructions to access a feature set and an occlusion set that are associated with an industrial facility. An occlusion path that intersects a detectable occlusion of the occlusion set and the sensor origin of the EBL sensor can be determined. A feature intersection of the occlusion path can be determined. A detectable feature can be classified as an occluded detectable feature based at least in part upon location of the feature intersection. The industrial vehicle can be navigated through the industrial facility utilizing the feature set exclusive of the occluded detectable feature.

Systems, methods, and industrial vehicles for determining the visibility of features

According to the embodiments described herein, a method for lost vehicle recovery utilizing associated feature pairs may include, for a materials handling vehicle determined to be lost, creating a plurality of associated feature pairs by retrieving a subsequent set of camera data from a camera comprising two-dimensional UV space information, forming pairs from the UV space information, and associating each formed pair with pairs from each of a plurality of three-dimensional global feature points of an industrial facility map. The method may further include calculating a best estimate pose from calculated vehicle poses of the associated feature pairs based on a highest-rated pair of the plurality of associated feature pairs, using an accumulated odometry to update the best estimate pose to a current localized position, updating the seed position as the current localized position, and operating the materials handling vehicle utilizing the updated seed position.

Lost vehicle recovery utilizing associated feature pairs

A method for coordinating path planning for one or more automated vehicles is described, including receiving an executable task for an automated vehicle, providing a multi-level graph comprising high-level nodes, connection nodes, roadmap nodes, and one or more local paths, constructing a grid corresponding with the multi-level graph, selecting grid squares corresponding to a start position, a goal position, or both if they are off the multi-level graph, determining joining paths from the start position, goal position, or both to the multi-level graph, constructing a solution set of roadmap graphs from the multi-level graph, selecting a coordinate path plan, communicating at least a portion of the coordinate path plan to each automated vehicle, and controlling the automated vehicle in accordance with the coordinate path plan.

Growing community of inventors

Auckland, New Zealand

Jacob Jay Thomson