Ford Global Technolgoies, LLC

Geoffrey Horowitz

Yifan Chen

Smruti Panigrahi

Kurt Michael Lundeen

Meghna Menon

Gregory P Linkowski

David Michael Herman

Daniel A Makled

Mario Anthony Santillo

Ling Zhu

Aaron Lesky

Pavithra Madhavan

Brian Quinn Kettlewell

Akshat Rajvanshi

Sarah Garrow

A method for controlling a plurality of autonomous mobile robots (AMRs) in a manufacturing environment having an intersection includes obtaining a plurality of routes associated with the plurality of AMRs, velocity information associated with the plurality of AMRs, and priority information associated with the plurality of AMRs, and determining a plurality of arrival times associated with the plurality of AMRs based on the velocity information and the plurality of routes. The method includes generating a plurality of intersection reservations based on the plurality of arrival times and the priority information, where each intersection reservation from among the plurality of intersection reservations corresponds to an AMR from among the plurality of AMRs, and controlling a movement of the plurality of AMRs through the intersection based on the plurality of intersection reservations.

Systems and methods for controlling autonomous mobile robots in a manufacturing environment

A system for detecting a road surface includes a processor programmed to identify, in a vehicle sensor field of view, environment features including a sky, a road surface, a road shoulder, based on map data and data received from the one or more vehicle sensors, upon determining a low confidence in identifying an area of the field of view to be a road surface or sky, to receive a polarimetric image, and to determine, based on the received polarimetric image, whether the identified area is a mirage phenomenon, a wet road surface, or the sky. The low confidence is determined upon determining that a road surface has a vanishing edge, a road lane marker is missing, or an anomalous object is present.

Vehicle sensor occlusion detection

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.

Method and system for positioning sensors within a workspace

Disclosed is an end-to-end delivery system that uses standard containers designed for autonomous vehicle (AV) goods delivery, a purpose-built AV cargo management system, a purpose-built robot to load and unload packages, and software to coordinate the various tasks involved. The standard containers may include a hardware locking interface for locking to a carrying robot. The cargo management system may include a programmable conveyor system installed on each floor of a multi-floor cargo space within the AV. For example, the floor may include a roller surface to allow omnidirectional routing of packages. An elevator shaft may be used for receiving and off-loading containers. The software may identify a target container anywhere within the multi-floor cargo space, and determine how to rearrange the containers within a grid in the AV so that the target container may be moved to the elevator shaft for unloading.

Container method and system for automated end-to-end package delivery

Systems and methods for delivering a package to a curbside receptacle are provided. A delivery window of a vehicle may be aligned with a curbside receptacle. A carousel within the vehicle may be moved, e.g., rotated, within the vehicle to align a target compartment with the delivery window. A conveyor arm slidably coupled to the delivery window is then extended and aligned with the target compartment, and a target package within the target compartment is ejected from the target compartment onto the conveyor arm, e.g., via a plunger mechanism. The conveyor arm then transfers the target package to curbside receptacle.

Automated systems and methods for transferring packages from a vehicle to a curbside locker box

A first distance dbetween a vehicle at a first location and an object is determined. A best fit line representing the object is determined from a plurality of sensor data. A distance &#x394;d to move to a second location is specified. A predicted second distance dbetween the vehicle at the second location and the object is determined based on the first distance d, the distance &#x394;d, and the best fit line. The vehicle is operated from the first location to the second location based on a center steering wheel angle. A measured second distance dbetween the vehicle at the second location and object is determined. Then the center steering wheel angle is one of (a) maintained based on the predicted second distance dmatching the measured second distance d, or (b) updated based on the predicted second distance dbeing different than the measured second distance d.

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Farmington Hills, MI, United States of America

Geoffrey Horowitz