Systems and methods for real time calibration of multiple range sensors on a robot

A robotic system for calibrating a plurality of sensors, comprising:

• a plurality of sensors coupled to the robotic system;
• a memory comprising computer readable instructions stored thereon;
• and
• at least one controller configured to execute the computer readable instructions to:
• receive a point cloud from a first sensor, wherein the point cloud comprises an aggregate of a sequence of scans captured from the first sensor, the scans each comprise a plurality of points;
• align points of each scan to their respective nearest neighboring points of subsequent or prior scans in the sequence of scans, wherein the alignment corresponds to a rotational transform, the alignment comprising a self-calibration;
• and
• apply the rotational transform to (i) data from the first sensor, and (ii) the point cloud.

A non-transitory computer readable storage medium comprising a plurality of computer readable instructions stored thereon which, when executed by at least one controller of a robot, cause the robot to:

• receive a point cloud from a first sensor, wherein the point cloud comprises an aggregate of a sequence of scans captured from the first sensor, the scans each comprise a plurality of points;
• align points of each scan to their respective nearest neighboring points of subsequent or prior scans in the sequence of scans, wherein the alignment corresponds to a rotational transform, the alignment comprising a self-calibration;
• and
• apply the rotational transform to (i) data from the first sensor, and (ii) the point cloud.

A robotic system for calibrating at least two sensors, comprising:

• at least two sensors coupled to the robotic system;
• a memory comprising computer readable instructions stored thereon;
• and
• at least one controller configured to execute the computer readable instructions to:
• receive a first point cloud from a first sensor of the at least two sensors, wherein the first point cloud comprises an aggregate of a sequence of scans captured from the first sensor, the scans each comprise a plurality of points;
• align points of each scan to their respective nearest neighboring points of subsequent or prior scans in the sequence of scans, wherein the alignment corresponds to a first rotational transform, the alignment comprising a self-calibration;
• apply the first rotational transform to (i) data from the first sensor, and (ii) the first point cloud;
• receive a second point cloud from a second sensor of the at least two sensors, wherein the second point cloud comprises an aggregate of a sequence of scans captured from the second sensor, the scans each comprise a plurality of points;
• align points of each scan to their respective nearest neighboring points of subsequent or prior scans in the sequence of scans, wherein the alignment corresponds to a second rotational transform, the alignment comprising a self-calibration;
• apply the second rotational transform to (i) data from the second sensor, and (ii) the second point cloud;
• calculate cross-sensor energy based on a cumulative distance between nearest neighboring points of the first point cloud and points of the second point cloud which are within a threshold distance to each other;
• cross-calibrate the first sensor by aligning the point cloud from the first sensor to a second point cloud from a second sensor via minimizing the cross-sensor energy, the first and second point cloud comprising an aggregate of sequential scans from the first and second sensor with first and second rotational transforms applied thereto respectively, the alignment yields a third transform comprising at least one of a translation or rotation;
• and
• apply the second transform to (i) data from the first sensor, and (ii) the point cloud of the first sensor.