Abstract: A method for remotely waking-up a vehicle includes the request of a vehicle power state of at least one non-responsive vehicle of a plurality of autonomously operated vehicles, the verification—via a remote-start-wakeup automated vehicle marshaling algorithm installed within an infrastructure—of a current power state of the at least one non-responsive vehicle, the identification that the at least one non-responsive vehicle is in an off-state, and the generation of a wake-up command that is wirelessly transmitted to the at least one non-responsive vehicle via a CV2X-PC5 protocol.

Abstract: A method for marshalling a vehicle includes: receiving signals from a set of infrastructure sensors associated with a vehicle management system; processing the signals from the set of infrastructure sensors and the signals from one or more sensors on-board the vehicle; sending the processed signals to the vehicle as one or more vehicle commands; receiving signals from the one or more sensors on-board the vehicle; and processing the one or more vehicle commands and the signals from the one or more sensors on-board the vehicle to generate new commands that are sent to the vehicle to marshal the vehicle to a location.

Abstract: A method for vehicle distribution of a fleet of vehicles includes: receiving signals from a set of infrastructure sensors; receiving signals from one or more sensors on-board the vehicles; processing the signals from the set of infrastructure sensors and the signals from the one or more sensors on-board the vehicles; controlling autonomous queuing of the vehicles using the processed signals; and controlling autonomous loading and unloading of the vehicles onto a transportation vehicle according to the queuing of the vehicles.

Abstract: A method of wirelessly communicating status information of one or more vehicles with one or more infrastructures including the receipt of an onboarding process trigger based on a current status associated with a pre-onboarding process of the one or more vehicles, the determination of a current status associated with an onboarding process of the one or more vehicles based on the onboarding process trigger and an autonomous vehicle marshaling algorithm, and the output of an indication corresponding to the current status associated with the onboarding process of the one or more vehicles via exterior lights of the one or more vehicles to the one or more infrastructures or one or more human operators.

Abstract: A method includes generating a workspace model having one or more digital robots, one or more digital sensors, and a digital transport system. The method includes simulating, for a task of the one or more digital robots, a sensor operation of the one or more digital sensors within the workspace model based on sensor characteristics of the one or more digital sensors. The method includes identifying, for the task of the one or more digital robots, an undetectable area within the workspace model based on the simulated sensor operation. The method includes selectively positioning, by a transport system, a set of sensors from among the one or more sensors based on the undetectable areas associated with the task.

Abstract: A method of managing a fleet of robots for delivery of materials in a facility is provided. The method includes: determining a sequence of waypoints by a Branch and Bound (B&B) method; determining a path through the sequence of waypoints by a dual graph method; determining distribution of tasks among the robots by the B&B method; and determining a fleet composition by the B&B method.

Abstract: A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive a command for a host vehicle to perform a maneuver, detect a target vehicle, minimize a cost function, determine a host control input for the host vehicle based on the minimization of the cost function, and actuate the host vehicle to perform the maneuver according to the host control input. The cost function includes a host cost and a target cost. The host cost is a cost associated with a host kinematic state of the host vehicle, and the target cost is a cost associated with a target kinematic state of the target vehicle.

Abstract: A method includes generating a workspace model having one or more digital robots, one or more digital sensors, and a digital transport system. The method includes simulating, for a task of the one or more digital robots, a sensor operation of the one or more digital sensors within the workspace model based on sensor characteristics of the one or more digital sensors. The method includes identifying, for the task of the one or more digital robots, an undetectable area within the workspace model based on the simulated sensor operation. The method includes selectively positioning, by a transport system, a set of sensors from among the one or more sensors based on the undetectable areas associated with the task.

Abstract: A method includes estimating, by a vehicle communication system, a vehicle-localized time based on a previous vehicle system time and at least one internal factor in response to a primary synchronization data not being received and in response to an auxiliary synchronization data not being received. The previous vehicle system time is based on at least one of a previous primary synchronization data or a previous auxiliary synchronization data. The method further includes synchronizing, by the vehicle communication system, a vehicle system time employed by one or more vehicle modules disposed in the vehicle based on one of the primary synchronization data received, the auxiliary synchronization data received, or the vehicle-localized time estimated.

Abstract: A method includes obtaining infrastructure data from one or more infrastructure sensors, determining an infrastructure-based positional characteristic of the vehicle based on the infrastructure data, obtaining onboard image data from the onboard image sensor, determining an image-based positional characteristic of the vehicle based on the onboard image data and a digital twin of the manufacturing environment, generating an offset matrix based on the infrastructure-based positional characteristic and the image-based positional characteristic, and selectively adjusting a rotation matrix of the onboard image sensor based on the offset matrix and one or more additional offset matrices.

Abstract: A method includes generating a workspace model having one or more robots and a plurality of image sensors, defining a plurality of pose scenarios of the one or more robots, and defining sensor characteristics of the plurality of image sensors. The method includes, for each of the plurality of pose scenarios, simulating a sensor operation of the plurality of image sensors within the workspace model based on the sensor characteristics and identifying an undetectable area within the workspace model based on the simulated sensor operation. The method includes performing a sensor placement control based on the undetectable areas associated with each of the plurality of pose scenarios.

Abstract: A system for reconfiguring a factory having equipment at different workstations throughout the factory and a plurality of sensors disposed throughout the factory includes a factory configuration module configured to store a plurality of predetermined factory configurations and a plurality of mobile transporters configured to engage and transport the equipment to the different workstations throughout the factory based on the predetermined factory configurations and dynamic inputs, where the dynamic inputs include a status of the equipment, a status of the plurality of mobile transporters, sensor data output by the plurality of sensors, or a combination thereof.

Abstract: A method for controlling vehicle movement includes: obtaining, by a vehicle, at least one radio frequency (RF) signal metric for a plurality of RF signals broadcasted in a manufacturing environment; broadcasting, by the vehicle, a vehicle message when the at least one RF signal metric satisfies at least one RF communication issue condition; generating, by an infrastructure system, an RF map based on the vehicle message and at least one additional vehicle message from at least one additional vehicle; and dynamically adjusting an infrastructure message, by the infrastructure system, based on the RF map when the vehicle autonomously navigates within the manufacturing environment.

Abstract: A system for calibrating a vehicle includes a funnel-type wheel alignment system and an infrastructure system. The infrastructure system is configured to autonomously control a movement of the vehicle within the funnel-type wheel alignment system based on an autonomous marshaling routine and selectively adjust one or more parameters of the autonomous marshaling routine based on one or more calibration metrics generated by the funnel-type wheel alignment system. The funnel-type wheel alignment system is configured to: obtain steering wheel angle data from one or more vehicle sensors, determine a vehicle steering pinion angle offset based on the steering wheel angle data, perform a physical alignment of one or more wheels of the vehicle as the vehicle moves through the funnel-type wheel alignment system, generate the one or more calibration metrics based on the vehicle steering pinion angle offset and the physical alignment, and broadcast the one or more calibration metrics.

Abstract: A method includes calculating, by a vehicle system, a pose information for a vehicle having the vehicle system, determining, by the vehicle system, whether the calculated pose information matches that of a vehicle pose information received from an infrastructure system, updating, by the vehicle system, a current pose of the vehicle based on the calculated pose information, transmitting, by the vehicle system, a notification regarding the inaccurate pose information to the infrastructure system, and controlling, by the vehicle system, movement of the vehicle based on a stored marshaling route until a stop condition is satisfied.

Abstract: A method for transmitting a request to join a marshaling convoy, receiving routing-localization information in response to the request, and controlling one or more sub-systems within a vehicle to enter a marshaling convoy based on the routing-localization information and a marshaling message, wherein the marshaling message causes the marshaling convoy to accommodate the vehicle.

Abstract: A method for the determination of pose information associated with a vehicle, the determination of a steering angle offset of the vehicle using an offset determination model configured to learn the steering angle offset of the vehicle, and the transmission of one or more steering angle offset commands to the vehicle.

Abstract: A vehicle-aided detection system for a vehicle is provided herein. The vehicle-aided detection system includes an end effector that is movable in an operating environment and coupled to a cargo bed via a robotic arm. A sensor system is configured to detect the end effector and at least one person in the operating environment. A controller is configured to process information received from the sensor system and to determine a physical profile of at least one person. The controller then determines whether user-worn equipment is equipped by the at least one person.

Abstract: A computer is programmed to identify first and second virtual boundaries of a roadway lane based on a predicted boundary between the roadway lane and an adjacent roadway lane, determine a first constraint value based on a first virtual boundary approach acceleration, determine a second constraint value based on a second virtual boundary approach acceleration, output a prescribed steering angle, brake input, and propulsion input when one of the constraint values violates a respective threshold, and actuate components to attain the prescribed steering angle, brake input, and propulsion input. The first virtual boundary approach acceleration is based on a steering wheel angle of a vehicle and input to one of a brake or a propulsion of the vehicle. The second virtual boundary approach acceleration is based on a steering wheel angle of the vehicle and input to one of a brake or a propulsion of the vehicle.

Abstract: A system for reconfiguring a factory having equipment at different workstations throughout the factory and a plurality of sensors disposed throughout the factory includes a factory configuration module configured to store a plurality of predetermined factory configurations and a plurality of mobile transporters configured to engage and transport the equipment to the different workstations throughout the factory based on the predetermined factory configurations and dynamic inputs, where the dynamic inputs include a status of the equipment, a status of the plurality of mobile transporters, sensor data output by the plurality of sensors, or a combination thereof.