Pony Ai Inc.

Stephen Lee

Pingfan Meng

Wei-Yang Chiu

Kai Chen

Yubo Zhang

Zhenhao Pan

Yuning Yang

A computing device triggers a sensor operation. The computing device includes one or more processors and instructions or logic that, when executed by the one or more processors, implements computing functions. The computing device performs receiving timestamps from a sensor, simulating an operation of the sensor, the simulation including predicting orientations of the sensor at different times based on the received timestamps, comparing a latest timestamp of the computing device to a latest timestamp of the sensor, and based on the comparison, triggering a second sensor to perform an operation.

Sensor triggering to synchronize sensor data

A computing device performs initial processing of sensor data. The computing device performs obtaining sensor data, writing the sensor data to first addresses of a dynamically allocated buffer associated with the computing device, encoding the sensor data, writing the encoded sensor data to second addresses of the dynamically allocated buffer, in response to completing the writing of the encoded sensor data, indicating that the writing of the encoded sensor data has been completed, receiving, from a computing resource, a polling request to read the encoded sensor data, transmitting, to the computing resource, a status that the writing of the encoded sensor data to the second addresses has been completed, reading, to a memory of the computing resource, the encoded sensor data, receiving, from the computing resource, a second status that the encoded sensor data has been read, and removing, from the dynamically allocated buffer, the encoded sensor data.

Efficient retrieval of sensor data while ensuring atomicity

A computing device performs initial processing of sensor data. The computing device includes one or more processors and instructions or logic that, when executed by the one or more processors, cause the computing device to perform obtaining sensor data, encoding the sensor data, writing the encoded sensor data to a dynamically allocated buffer, and logging a status of the written encoded sensor data at a static location of the dynamically allocated buffer. The status includes any one or more of memory addresses at which frames of the sensor data begin in the dynamically allocated buffer, valid bit fields corresponding to the frames, and sizes of each of data segments within the frames. The instructions further cause the computing device to perform, in response to receiving a polling request from a computing resource, transmitting the logged status to the computing resource.

Efficient retrieval of sensor data

Described herein are systems, methods, and non-transitory computer readable media for constructing and utilizing vehicle field-of-view (FOV) information. The FOV information can be utilized in connection with vehicle localization such as localization of an autonomous vehicle (AV), sensor data fusion, or the like. A customized computing machine can be provided that is configured to construct and utilize the FOV information. The customized computing machine can utilize the FOV information, and more specifically, FOV semantics data included therein to manage various data and execution patterns relating to processing performed in connection with operation of an AV such as, for example, data prefetch operations, reordering of sensor data input streams, and allocation of data processing among multiple processing cores.

Systems and methods for constructing and utilizing field-of-view (FOV) information

Described herein are systems, methods, and non-transitory computer readable media for triggering a sensor operation of a second sensor (e.g., a camera) based on a predicted time of alignment with a first sensor (e.g., a LiDAR), where operation of the second sensor is simulated to determine the predicted time of alignment. In this manner, the sensor data captured by the two sensors is ensured to be substantially synchronized with respect to the physical environment being sensed. This sensor data synchronization based on predicted alignment of the sensors solves the technical problem of lack of sensor coordination and sensor data synchronization that would otherwise result from the latency associated with communication between sensors and a centralized controller and/or between sensors themselves.

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Fremont, CA, United States of America

Stephen Lee