- Mountain View CA, US Alexander Rashid Ansari - San Francisco CA, US
International Classification:
G05D 1/02 G06V 20/58 G06K 9/00
Abstract:
Systems and methods are provided for detecting objects of interest. A computing system can input sensor data to one or more first machine-learned models associated with detecting objects external to an autonomous vehicle. The computing system can obtain as an output of the first machine-learned models, data indicative of one or more detected objects. The computing system can determine data indicative of at least one uncertainty associated with the one or more detected objects and input the data indicative of the one or more detected objects and the data indicative of the at least one uncertainty to one or more second machine-learned models. The computing system can obtain as an output of the second machine-learned models, data indicative of at least one prediction associated with the one or more detected objects. The at least one prediction can be based at least in part on the detected objects and the uncertainty.
- San Francisco CA, US Chaoqun Tao - Emeryville CA, US Anny Xinda Yang - San Francisco CA, US Christopher James Lyons - Oakland CA, US Bryan John Nagy - Allison Park PA, US Quinn Zikun Shen - San Francisco CA, US Michael Beeheng Goff - San Mateo CA, US Alexander Rashid Ansari - San Francisco CA, US Qing Li - Union City CA, US
A vehicle navigation system may include a data pipeline that proposes routing graph modifications from automatically ingested data sources and that provides enough context to suggest an expiration time to remove the routing graph modifications once imposed. The system and method receives from at least one data source routing graph modification data including geographic location data identifying a location to which a routing graph modification applies. The routing graph modification data is associated with one or more roadway elements in a routing graph of a navigation constraints system, and the routing graph modification data associated with the one or more roadway elements is classified as a routing graph modification. The routing graph modification is added to or, if expired, removed from the navigation constraints system.
Providing Actionable Uncertainties In Autonomous Vehicles
- San Francisco CA, US Alexander Rashid Ansari - San Francisco CA, US
International Classification:
G05D 1/02 G06K 9/00
Abstract:
Systems and methods are provided for detecting objects of interest. A computing system can input sensor data to one or more first machine-learned models associated with detecting objects external to an autonomous vehicle. The computing system can obtain as an output of the first machine-learned models, data indicative of one or more detected objects. The computing system can determine data indicative of at least one uncertainty associated with the one or more detected objects and input the data indicative of the one or more detected objects and the data indicative of the at least one uncertainty to one or more second machine-learned models. The computing system can obtain as an output of the second machine-learned models, data indicative of at least one prediction associated with the one or more detected objects. The at least one prediction can be based at least in part on the detected objects and the uncertainty.
Dec 2, 2009 ... Welcome to the official Facebook Page of Alexander Ansari (Dynamishots Photography). Get exclusive content and interact with Alexander ...
Welcome to the official Facebook Page of Alexander Ansari (Dynamishots Photography). Get exclusive content and interact with Alexander Ansari (Dynamishots ...