A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators

Sensors

Gabriele Ligorio¹  Angelo Maria Sabatini² 

[1] The BioRobotics Institute, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, Pisa 56125, Italy

关键词: simulation;    sensor modeling;    sensor fusion;    performance evaluation;   

DOI  :  10.3390/s151229903

来源: mdpi

【 摘 要 】

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.