PRIORITY CLAIM

This application is based upon and claims the right of priority under 35 U.S.C. § 371 to International Application No. PCT/US2017/060295 filed on Nov. 7, 2017, which is incorporated by reference herein.

FIELD

The present disclosure relates generally to updating a sensor based on sensor data and the semantic state associated with an area.

BACKGROUND

Object detection systems can capture a variety of information about the objects in an environment, including, for example the appearance of the objects. Associating aspects of a detected object (e.g., the appearance of the object) with another piece of information such as the type of object can be useful in various applications. However, many existing object detection systems require a great deal of manual analysis and input, which can be burdensome. Further, many of the existing systems used to analyze areas are either wasteful of resources due to excessive updating of areas that have not changed or inaccurate due to not providing an up to date representation of the areas. Accordingly, there exists a demand for an effective way to update information associated with the state of an environment.

SUMMARY

Aspects and advantages of embodiments of the present disclosure will be set forth in part in the following description, or may be learned from the description, or may be learned through practice of the embodiments.

One example aspect of the present disclosure is directed to a method of updating a sensor based on sensor data and the semantic state associated with an area. The method can include receiving, by a computing system that includes one or more computing devices, sensor data based in part on one or more sensor outputs from one or more sensors. The sensor data can include information associated with one or more states of one or more areas detected by the one or more sensors. The method can include generating, by the computing system, based in part on the sensor data, an estimated semantic state of an area of the one or more areas from a target sensor that can detect the one or more states of the one or more areas. The method can include determining, by the computing system, based in part on a comparison of the estimated semantic state to one or more semantic states of the area from the one or more sensors, an uncertainty level associated with an accuracy of the estimated semantic state. Further, the method can include, responsive to the uncertainty level satisfying one or more update criteria, obtaining, by the computing system, an updated version of the sensor data from the target sensor.

Another example aspect of the present disclosure is directed to one or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations. The operations can include receiving sensor data based in part on one or more sensor outputs from one or more sensors. The sensor data can include information associated with one or more states of one or more areas detected by the one or more sensors. The operations can include generating, based in part on the sensor data, an estimated semantic state of an area of the one or more areas from a target sensor that can detect the one or more states of the one or more areas. The operations can include determining, based in part on a comparison of the estimated semantic state to one or more semantic states of the area from the one or more sensors, an uncertainty level associated with an accuracy of the estimated semantic state. Further, the operations can include, responsive to the uncertainty level satisfying one or more update criteria, obtaining an updated version of the sensor data from the target sensor.

Another example aspect of the present disclosure is directed to a computing system comprising one or more processors, and one or more non-transitory computer-readable media storing instructions that when executed by the one or more processors cause the one or more processors to perform operations. The operations can include receiving sensor data based in part on one or more sensor outputs from one or more sensors. The sensor data can include information associated with one or more states of one or more areas detected by the one or more sensors. The operations can include generating, based in part on the sensor data, an estimated semantic state of an area of the one or more areas from a target sensor that can detect the one or more states of the one or more areas. The operations can include determining, based in part on a comparison of the estimated semantic state to one or more semantic states of the area from the one or more sensors, an uncertainty level associated with an accuracy of the estimated semantic state. Further, the operations can include, responsive to the uncertainty level satisfying one or more update criteria, obtaining an updated version of the sensor data from the target sensor.

Other example aspects of the present disclosure are directed to other computer-implemented methods, systems, apparatus, tangible, non-transitory computer-readable media, user interfaces, memory devices, and electronic devices for updating a sensor based on sensor data and the semantic state associated with an area.

These and other features, aspects and advantages of various embodiments will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the related principles.

