Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers

Research Article

Relative Translation and Rotation Calibration Between Optical Target and Inertial Measurement Unit

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  • @INPROCEEDINGS{10.1007/978-3-319-61563-9_15,
        author={Manthan Pancholi and Svilen Dimitrov and Norbert Schmitz and Sebastian Lampe and Didier Stricker},
        title={Relative Translation and Rotation Calibration Between Optical Target and Inertial Measurement Unit},
        proceedings={Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers},
        proceedings_a={S-CUBE},
        year={2017},
        month={7},
        keywords={Relative pose calibration Inertial measurement unit Tracking calibration Genetic algorithm},
        doi={10.1007/978-3-319-61563-9_15}
    }
    
  • Manthan Pancholi
    Svilen Dimitrov
    Norbert Schmitz
    Sebastian Lampe
    Didier Stricker
    Year: 2017
    Relative Translation and Rotation Calibration Between Optical Target and Inertial Measurement Unit
    S-CUBE
    Springer
    DOI: 10.1007/978-3-319-61563-9_15
Manthan Pancholi1,*, Svilen Dimitrov1,*, Norbert Schmitz1,*, Sebastian Lampe2, Didier Stricker1,*
  • 1: German Research Center for Artificial Intelligence
  • 2: Volkswagen Group Research
*Contact email: manthan.pancholi@dfki.de, svilen.dimitrov@dfki.de, norbert.schmitz@dfki.de, didier.stricker@dfki.de

Abstract

Cameras and Inertial Measurement Units are widely used for motion tracking and general activity recognition. Sensor fusion techniques, which employ both Vision- and IMU-based tracking, rely on their precise synchronization in time and relative pose calibration. In this work, we propose a novel technique for solving both time and relative pose calibration between an optical target (OT) and an inertial measurement unit (IMU). The optical tracking system gathers 6 position and rotation data of the OT and the proposed approach uses them to simulate accelerometer and gyroscope readings to compare them against real ones recorded from the IMU. Convergence into the desired result of relative pose calibration is achieved using the adaptive genetic algorithm.