The aim of this paper is to presents a comparison among three different algorithms of sensor data fusion based on Inertial Measurement Unit (IMU) looking at how they influence the energy consumption in an IMU platform. Complementary filter, Kalman filter and Quaternion filter have been considered for the aim using a low-cost platform equipped with Micro-Electro-Mechanical-system (MEMS) as gyroscope, accelerometer and magnetometer. The energy consumptions have been measured during both static and dynamic operations, using the industry-standard CoreMark performance benchmark with the ULPMark line of ultra-low-power benchmarks, reporting the difference among the considered algorithms.
Energy Characterization of Attitude Algorithms
Salvatore Dello Iacono;
2019-01-01
Abstract
The aim of this paper is to presents a comparison among three different algorithms of sensor data fusion based on Inertial Measurement Unit (IMU) looking at how they influence the energy consumption in an IMU platform. Complementary filter, Kalman filter and Quaternion filter have been considered for the aim using a low-cost platform equipped with Micro-Electro-Mechanical-system (MEMS) as gyroscope, accelerometer and magnetometer. The energy consumptions have been measured during both static and dynamic operations, using the industry-standard CoreMark performance benchmark with the ULPMark line of ultra-low-power benchmarks, reporting the difference among the considered algorithms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
