Trimble Inc.

Adam Clare

Shawn D Weisenburger

Gleb Aleksandrovich Zyryanov

Scott Crozier

John Boss

Jon McKendry

Ethan William Moe

Geoffrey Kirk

Yu Jiao

Greg Wallace

Ethan Moe

Megan Marotz

Described herein is a visual indication system implemented on a mobile machine. The visual indication system at least partially surrounds the mobile machine and includes a plurality of displayable regions. Objects surrounding the mobile machine are detected using an object detection sensor. A direction with respect to the mobile machine is detected for each of the objects. A current state of the mobile machine is determined. An object-directed indicator for each of the objects is generated based on the current state of the mobile machine. The object-directed indicator for each of the objects is displayed on the visual indication system at a particular displayable region based on the direction of the particular object.

Visual indication system for mobile machines

Construction vehicles using a teach and repeat system can ascertain boundaries of a task area while working, without knowing a perimeter of the task area before starting the task. The system maps a first path of the vehicle by recording a position of a vehicle moving from a first start position to a first end position. A second path is predicted, based on a shape of the first path, the second path having a second start position and a second end position. A third path is mapped from a third start position to a third end position. Boundaries of the task area are ascertained based on the first path, the first start position, the second start position, the third start position, the third path, the first end position, the second end position, and the third end position.

Determination of task area boundaries during driver-assisted construction vehicle operation

A receiver system for determining coordinates of a location can include two GNSS receiver antennas positioned in fixed relation to each other and separated by a short baseline. Signals received from the two receiver antennas can be processed to define a 'virtual' antenna located at the midpoint between the two receiver antennas. For instance, a location can be determined for each receiver antenna using GNSS-based techniques, and the locations of the two antennas can be used to determine a location of the virtual antenna. As another example, GNSS observables from the two antennas can be combined to provide a set of “virtual” observables for the virtual antenna, and GNSS-based techniques can be applied to the virtual observables to determine a location of the virtual antenna.

GNSS location determination using a virtual antenna

Disclosed are a method and apparatus are provided for determining the amount of obstruction of a view of a satellite. An estimated satellite location from a satellite signal is mapped to a matrix of obstructions. A window is determined around the satellite location and all the obstructions within the window are considered in determining whether the satellite is obstructed, with the window considering the degree of possible error within the various measurements. In embodiments, the window size if varied based on the estimated amount of error and location of the satellite within the matrix.

Mitigating errors in GNSS with upward facing sensor

Various embodiments provide novel tools and techniques for photogrammetric machine measure-up, including without limitation solutions that can be used for excavation and similar applications. A system includes a machine, a user device may further comprise an image sensor, an accelerometer, a processor, and a computer readable medium in communication with the processor, the computer readable medium having encoded thereon a set of instructions executable by the processor to photogrammetrically measure-up the machine. Photogrammetric measure-up includes capturing, via the image sensor, two or more target images of each of the two or more targets, the two or more target images including a first target image and a second target image, and determining a measurement between two of the two or more reference features of the machine based on a first target image and second target image.

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Broomfield, CO, United States of America

Adam Clare