Sensor Calibration, Modeling, and Simulation

Living reference work entry

Abstract

For humanoid robots, sensors are a critical aspect of the entire robot system because they are responsible for accurately perceiving the environment. Due to the cost of real experiments on humanoids, sensor modeling and simulation play important roles in robotics research. For applications in the real world, sensor calibration is the prerequisite for sensors to function properly, and this chapter begins with a review of general problems in sensor calibration, modeling, and simulation. An often used formulation of sensor calibration in robotics and computer vision is “AX = XB,” where A, X, and B are rigid-body transformations with A and B given from sensor measurements and X is the unknown rigid-body transformation to be calibrated. Many methods have been proposed to solve X given data streams of A and B under different scenarios. This chapter presents the most complete picture of the AX = XB solvers to date. First, a brief overview of the various important sensor calibration techniques is given and problems of interest are highlighted. Then, a detailed review of the various “AX = XB” algorithms is presented. The notations used in different algorithms are unified to show the interconnections between the selected methods in a straightforward way. Finally, the criterion for data selection and various error metrics are introduced, which are of critical importance for evaluating the performance of AX = XB solvers.

Keywords

Sensor calibration Hand-eye calibration Humanoid robot Review 

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Robot and Protein Kinematics Laboratory, Laboratory for Computational Sensing and Robotics, Department of Mechanical EngineeringThe Johns Hopkins UniversityBaltimoreUSA

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