Deep learning system

A computer-readable storage medium storing instructions executable by a processor to cause the processor to:

• provide the first sensor data as an input to a first portion of a machine learning model;
• provide the second sensor data as an input to a second portion of the machine learning model, wherein the machine learning model comprises a concatenator and a set of fully-connected layers, the first sensor data is of a first type generated by a device, and the second sensor data is of a different, second type generated by the device, wherein the concatenator takes an output of the first portion of the machine learning model as a first input and takes an output of the second portion of the machine learning model as a second input, and an output of the concatenator is provided to the set of fully-connected layers;
• and
• generate, from the first data and second data, an output of the machine learning model comprising a pose of the device within an environment.

A method comprising:

• providing the first sensor data as an input to a first portion of a machine learning model;
• providing the second sensor data as an input to a second portion of the machine learning model, wherein the machine learning model comprises a concatenator and a set of fully-connected layers, the first sensor data is of a first type generated by a device, and the second sensor data is of a different, second type generated by the device, wherein the concatenator takes an output of the first portion of the machine learning model as a first input and takes an output of the second portion of the machine learning model as a second input, and an output of the concatenator is provided to the set of fully-connected layers;
• and
• generating, from the first data and second data, an output of the machine learning model comprising a pose of the device within an environment.

A system comprising:

• a processor;
• a memory;
• a set of sensors;
• and
• a machine learning engine, executable by the processor to:
• access first sensor data generated by the set of sensors;
• provide the first sensor data as an input to a first portion of a machine learning model;
• access second sensor data generated by the set of sensors;
• provide the second sensor data as an input to a second portion of the machine learning model, wherein the machine learning model comprises a concatenator and a set of fully-connected layers, the first sensor data is of a first type generated by the set of sensors, and the second sensor data is of a different, second type generated by the set of sensors, wherein the concatenator takes an output of the first portion of the machine learning model as a first input and takes an output of the second portion of the machine learning model as a second input, and an output of the concatenator is provided to the set of fully-connected layers;
• and
• generate, from the first data and second data, an output of the machine learning model comprising a pose of the device within an environment.