Three-dimensional object detection

A non-transitory computer-readable storage device including program instructions executable by one or more processors that, when executed, cause the one or more processors to perform operations for an object in an environment, the operations comprising:

• obtaining, from one or more sensors, distance measurements from the one or more sensors to the object;
• generating a voxel representation of a three-dimensional space that includes the object;
• associating data values with voxels from the voxel representation of the three-dimensional space using the distance measurements, wherein each of the data values indicates whether presence of the object is detected in a respective one of the voxels, a first group of the data values for a first group of the voxels indicate that each of the first group of the voxels is a filled voxel in which the presence of the object is detected, and a second group of the data values for a second group of the voxels in which the presence of the object is not detected indicate a distance to one of the filled voxels;
• identifying object features in the voxel representation of the three-dimensional space based on the data values using a neural network;
• comparing the object features to pre-defined three-dimensional templates to generate scores that represent correspondence of the object features to the pre-defined three-dimensional templates;
• and
• determining a location and a rotational orientation for a three-dimensional object based on the scores.

A system for detecting an object in an environment, the system comprising:

• one or more sensors;
• a memory;
• and
• a processor configured to execute instructions stored in the memory, wherein the instructions, when executed, cause the processor to:
• obtain, from the one or more sensors, distance measurements from the one or more sensors to the object,
• generate a voxel representation of a three-dimensional space that includes the object,
• associate data values with voxels from the voxel representation of the three-dimensional space using the distance measurements, wherein each of the data values indicates whether presence of the object is detected in a respective one of the voxels, a first group of the data values for a first group of the voxels indicate that each of the first group of the voxels is a filled voxel in which the presence of the object is detected, and a second group of the data values for a second group of the voxels in which the presence of the object is not detected indicate a distance to one of the filled voxels,
• identify object features in the voxel representation of the three-dimensional space based on the data values using a neural network,
• compare the object features to pre-defined three-dimensional templates to generate scores that represent correspondence of the object features to the pre-defined three-dimensional templates, and
• determine a location and a rotational orientation for a three-dimensional object based on the scores.