Streaming object detection within sensor data

A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to implement:

• a partitoner that partitions a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by a sensing system that rotationally senses an environment constitutes a complete rotational sensing of the environment, and generates, for each sub-period, current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment;
• and
• an object detection neural network that processes, for each sub-period, the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment, wherein the object detection neural network comprises:
• a sequential processing subnetwork that processes (i) a current sequential processing subnetwork input and (ii) a preceding sequential processing subnetwork output that is generated by the sequential processing subnetwork from a preceding sub-period, to generate a current sequential processing subnetwork output;
• and
• an object detection subnetwork that processes, for the current data received, (i) the current sequential processing subnetwork output and (ii) a preceding object detection output that is generated by the object detection subnetwork from the preceding sub period, to generate the current object detection output.

One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by a sensing system that rotationally senses an environment constitutes a complete rotational sensing of the environment;
• for each sub-period:
• receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment;
• processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment, wherein the object detection neural network comprises:
• a sequential processing subnetwork that processes (i) a current sequential processing subnetwork input and (ii) a preceding sequential processing subnetwork output that is generated by the sequential processing subnetwork from a preceding sub-period, to generate a current sequential processing subnetwork output;
• and
• an object detection subnetwork that processes, for the current data received, (i) the current sequential processing subnetwork output and (ii) a preceding object detection output that is generated by the object detection subnetwork from the preceding sub period, to generate the current object detection output.