A Kalman Filter Approach to the Fusion of Acceleration, GNSS position and Rotation Sensor Data from Robot Motions

GNSS data:

Instrument: Javad antenna and Septentrio receiver

sampling rate: 100 Hz

Bandwidth of loop filter: auto adjust

Relative positioning 

Baseline: ultra short with distance of 5 m

files in Rinex format: Rover (moving antenna) and Base (stationary antenna), .20G (GLONASS Navigation data), .20N (GPS Navigation data), .20L (Galileo Navigation data), .20O (Observations)

Accelerometer data:

Instrument: EpiSensor and Centaur Digitizer

Sampling rate: 250 Hz

Unit: counts

unfiltered

file: XKUK_centaur-6_1233_20200908_114500.seed

Angular rate data:

Instrument: IMU KvH 1750 (includes accelerometer and rotational sensor)

Sampling rate: 250 Hz

Unit gyro: rad/s

Unit accelerometer: g (gravitational acceleration)

file: LOGGING_1750_IMU_1308K004_11_57_25_250.csv

Robot Feedback:

Instrument: KUKA model AGILUS KR 6 R900 sixx

Sampling rate: 250 Hz

Unit translation: m

Unit rotation: degree

files: kuka_motion_*.txt, 1-4 are consecutive in time.

Experiments:

T: translations, R: rotations, XL, L, S denote the relative amplitudes

10 experiments: TLRXL, TLRXL, TLRL, TLRL, TLRS, unfinished TLRS, TLRS, TLRS, TSRS, TSRS (Robot feedback (1,2), angular rate, GNSS data)

9 experiments: TLRXL, TLRXL, TLRL, TLRL, TLRS, unfinished TLRS, TLRS, TSRS, TSRS (Robot feedback (3,4), accelerometer data