Larry D Felser

58943102, Apr 13, 1999

Apr 19, 1996

8/635293

David Arsenault - Ithaca NY
David Phelan - Marietta GA
Larry Felser - Ithaca NY

Visionary Design Systems, Inc. - Santa Clara CA

G06T 100

345433

Shapes and solids modeled by a 3-D computer graphics system have "intelligence", i. e. , the shape typically includes a wide variety of characteristics in addition to geometric (e. g. , size and positional) information. These additional characteristics permit a user to manipulate 3-D shapes intuitively using a graphical user interface providing "drag and drop" capabilities--reducing the number of factors the user must worry about, saving a lot of time and user frustration, and allowing even non-technical, unskilled users to rapidly and efficiently create impressive images. A component-based architecture may expose any of multiple, alternate representations of the same shape depending on the particular need or application to provide an "intelligent load" that is especially powerful and advantageous in remote interactive imaging applications (e. g. , via the Internet) where data transfer and/or load times must be minimized. The shape architecture is hierarchical and extensible--providing great flexibility and expandability.

20190049960, Feb 14, 2019

Aug 10, 2017

15/673936

- Seattle WA, US
James Christopher Curlander - Mercer Island WA, US
Larry Felser - Bellevue WA, US
Gur Kimchi - Bellevue WA, US
Pragyana K. Mishra - Seattle WA, US

G05D 1/00
G01C 21/36

Systems and methods for operating autonomous vehicles are described. An autonomous vehicle may detect strategy modes and/or actions of other vehicles in a local environment. The autonomous vehicle may then select a strategy mode for its operations based on the detected strategy modes and/or actions of other vehicles, and based on an operational goal for the autonomous vehicle. The strategy modes may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The autonomous vehicle may further select an action for its operations based on the selected strategy mode.

20190049961, Feb 14, 2019

Aug 10, 2017

15/673945

- Seattle WA, US
James Christopher Curlander - Mercer Island WA, US
Larry Felser - Bellevue WA, US
Gur Kimchi - Bellevue WA, US
Pragyana K. Mishra - Seattle WA, US

G05D 1/00
G05D 1/02

Systems and methods for determining strategy modes for autonomous vehicles are described. An autonomous vehicle may detect aspects of other vehicles and aspects of the environment using one or more sensors. The autonomous vehicle may then determine strategy modes of the other vehicles, and select a strategy mode for its own operation based on the determined strategy modes and an operational goal for the autonomous vehicle. The strategy modes may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The autonomous vehicle may further determine elements in the environment and topological constraints associated with the environment, and select the strategy mode for its own operation based thereon.

20190049997, Feb 14, 2019

Aug 10, 2017

15/673952

- Seattle WA, US
James Christopher Curlander - Mercer Island WA, US
Larry Felser - Bellevue WA, US
Gur Kimchi - Bellevue WA, US
Pragyana K. Mishra - Seattle WA, US

G05D 1/02
G08G 1/00
G05D 1/00
G07C 5/00
G06Q 10/04

Systems and methods for coordinating operations of a plurality of autonomous vehicles are described. An autonomous vehicle management system may receive information from the plurality of autonomous vehicles related to strategy modes, actions, and the environments. The strategy modes may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The autonomous vehicle management system may then process the received information based on an operational goal for the system as a whole. The autonomous vehicle management system may then instruct modifications to operations of one or more of the plurality of autonomous vehicles to achieve the operational goal for the system.

20190051061, Feb 14, 2019

Aug 10, 2017

15/673925

- Seattle WA, US
James Christopher Curlander - Mercer Island WA, US
Larry Felser - Bellevue WA, US
Gur Kimchi - Bellevue WA, US
Pragyana K. Mishra - Seattle WA, US

G07C 5/00
G05D 1/00
H04H 20/65
G05D 1/02

Systems and methods for broadcasting strategy modes of autonomous vehicles are described. An autonomous vehicle may include one or more notification devices that broadcast a selected strategy mode for the autonomous vehicle. The selected strategy mode may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The notification devices may include visual, audio, or signal notification devices. In addition, the autonomous vehicle may broadcast other information associated with the vehicle, such as a position, a velocity, a priority, or an identity of the vehicle.