Robust sensor fusion for robot attitude estimation
Philipp Allgeuer, Sven Behnke
- 发表年份
- 2014
- 引用次数
- 10
摘要
Knowledge of how a body is oriented relative to the world is frequently invaluable information in the field of robotics. An attitude estimator that fuses 3-axis gyroscope, accelerometer and magnetometer data into a quaternion orientation estimate is presented in this paper. The concept of fused yaw, used by the estimator, is also introduced. The estimator, a nonlinear complementary filter at heart, is designed to be uniformly robust and stable-independent of the absolute orientation of the body-and has been implemented and released as a cross-platform open source C++ library. Extensions to the estimator, such as quick learning and the ability to deal dynamically with cases of reduced sensory information, are also presented.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002