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