The high quality of heading orientation is a key factor to monitor the industrial robot arms in the Industry 4.0. The paper proposes a new algorithm ‘No Motion No Integration’ (NMNI) to enhance the gyroscope performance via signal processing and specifically improve the Madgwick filter for heading estimation to overcome the weakness of magnetometer and Global Navigation Satellite System (GNSS). The experiment was carried out to characterize the pros and cons of traditional Madgwick and new approached Madgwick. The results show that the proposed method displayed high effective measurements. The gyroscope drift was minimized to attain a good yaw angle without a magnetometer or GNSS.
Pre-Processing Technique for Compass-less Madgwick filter in Heading Estimation for Industry 4.0 Robotics
Salvatore Dello Iacono;
2020-01-01
Abstract
The high quality of heading orientation is a key factor to monitor the industrial robot arms in the Industry 4.0. The paper proposes a new algorithm ‘No Motion No Integration’ (NMNI) to enhance the gyroscope performance via signal processing and specifically improve the Madgwick filter for heading estimation to overcome the weakness of magnetometer and Global Navigation Satellite System (GNSS). The experiment was carried out to characterize the pros and cons of traditional Madgwick and new approached Madgwick. The results show that the proposed method displayed high effective measurements. The gyroscope drift was minimized to attain a good yaw angle without a magnetometer or GNSS.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
