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A General Framework for Temporal Calibration of Multiple Proprioceptive and Exteroceptive Sensors

  • Jonathan Kelly
  • Gaurav S. Sukhatme
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 79)

Abstract

Fusion of data from multiple sensors can enable robust navigation in varied environments.However, for optimal performance, the sensors must be calibrated relative to one another. Full sensor-to-sensor calibration is a spatiotemporal problem: we require an accurate estimate of the relative timing of measurements for each pair of sensors, in addition to the 6-DOF sensor-to-sensor transform. In this paper, we examine the problem of determining the time delays between multiple proprioceptive and exteroceptive sensor data streams. The primary difficultly is that the correspondences between measurements from different sensors are unknown, and hence the delays cannot be computed directly. We instead formulate temporal calibration as a registration task. Our algorithm operates by aligning curves in a three-dimensional orientation space, and, as such, can be considered as a variant of Iterative Closest Point (ICP). We present results from simulation studies and from experiments with a PR2 robot, which demonstrate accurate calibration of the time delays between measurements from multiple, heterogeneous sensors.

Keywords

Iterative Close Point Multiple Sensor Temporal Calibration Iterative Close Point Calibration Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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