Torc Robotics, Inc.

The Charles Machine Works, Inc.

Ryan Chilton

Richard Felix Sharp

Michael Avitabile

Benjamin Hastings

David C Conner

Wade Foster

Gowtham Raj Gunaseela Udayakumar

Harish Pullagurla

Jason Harper

Zachary Miller

Karan Vivek Bhargava

Systems and methods for path planning for autonomous vehicles err on the side of a safer road position and safer type of collision if one were to occur. An autonomous vehicle perception module detects target objects within a region of interest (ROI). An autonomous vehicle processor estimates relative velocity between the ego vehicle and target objects, and estimates mass of target objects. Collision-aware path planning calculates a cost function that assigns higher costs for paths that take the vehicle close to objects that have a large velocity difference and higher costs for objects with large estimated mass. Path planning provides a cost map that yields a path that has appropriate buffer distances between the autonomous vehicle and surrounding objects. In the event the ego vehicle balances buffer distance margins to multiple surrounding target objects, target objects that would create more severe collisions are given greater buffer distance.

Collision aware path planning systems and methods

A method comprises monitoring, by a processor, using a sensor of a first vehicle, data associated with a retroreflective feature near a road being driven by the first vehicle; vectorizing, by the processor, the data associated with the retroreflective feature; generating, by the processor, a digital map including vectorized data associated with the retroreflective feature and a location associated with the retroreflective feature; receiving, by the processor, data associated with the retroreflective feature from a second vehicle; and executing, by the processor, a localization protocol to identify a location of the second vehicle using the digital map.

Detection and mapping of generalized retroreflective surfaces

Disclosed herein are methods and systems (sensors) that allow revision of HD maps for lane lines as the lane lines are created. In a non-limiting example, a method comprises receiving, by a processor from a sensor associated with a vehicle configured to paint a lane line, a color attribute, a patterns attribute, and a location of a lane line painted on a road by the vehicle; determining, by the processor, using the location received from the sensor, whether the road has an existing lane line; and revising, by the processor, a high definition map associated with at least one autonomous vehicle by removing the existing lane line from the high definition map and inserting the lane line in the high definition map.

Methods and systems for high definition map generation

Disclosed herein are methods and systems to provide intelligent display for vehicles including a method that comprises determining data associated a road sign; retrieving driving data associated with a vehicle; generating, using the driving data and data associated with the road sign, a graphical overlay presenting a virtual object corresponding to the trajectory of the vehicle or data associated with the vehicle; and presenting on an electronic device associated with the vehicle, the graphical overlay while the electronic device is presenting an image of a surrounding of the vehicle, wherein the graphical overlay is superimposed upon an image of the road sign.

Enhanced signage display for autonomous vehicles and passengers

Disclosed herein are methods and systems to provide intelligent display for vehicles including a method that comprises determining, by a processor, that a current trajectory of an autonomous vehicle includes a revised road condition having at least one attribute; retrieving, by the processor using the at least one attribute, a graphical overlay corresponding to the revised road condition; and displaying, by the processor on an electronic device associated with the autonomous vehicle, the graphical overlay while the electronic device is presenting an image of a surrounding of the autonomous vehicle.

Enhanced map display for autonomous vehicles and passengers

A detection system used to alert an operator of a work machine of humans or objects dangerously close to the machine or a work tool attached to the machine. The detection system uses one or more cameras to capture images of an area surrounding the machine. The captured images are displayed on an interface electronically connected to a processor. Prior to operation, one or more zones surrounding the work tool or work machine are defined and projected on the images displayed on the interface. The processor analyzes the images captured by the cameras and determines if a characteristic of a predetermined object is within one or more of the identified zones. If the processor determines the characteristic of the predetermined object is within one of the zones, the processor will identify the object on the display and trigger a warning system to alert to the operator to take necessary precautions.

Growing community of inventors

Blacksburg, VA, United States of America

Ryan Chilton