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This work proposes a fusion of inertial measurement units (IMUs) and a visual tracking system on an embedded device. The sensor-to-sensor calibration and the pose estimation are both achieved through an unscented Kalman filter (UKF). Two approaches for a UKF-based pose estimation are presented: The first uses the estimated pose of the visual SLAM system as measurement input for the UKF; The second...
It is well known in a Bayesian filtering framework, the use of inertial sensors such as accelerometers and gyroscopes improves 3D tracking performance compared to using camera measurements only. The performance improvement is more evident when the camera undergoes a high degree of motion. However, it is not well known whether the inertial sensors should be used as control inputs or as measurements...
The vision tracking system in this paper estimates the robot position relative to a target and rotates the camera towards the target. To estimate the robot position of mobile robot, the system combines information from an accelerometer, a gyroscope, two encoders, and a vision sensor. The encoders can provide fairly accurate robot position information, but the encoder data are not reliable when robot...
This paper presents an indoor navigation scheme for a skid-steering mobile robot using a low-cost gyro sensor and a monocular camera. Based on the kinematic model under nonholonomic constraint, a motion controller is designed, and so as to account for some uncertainties from the wheel-ground friction and slip, the rotational velocity measurement from a gyro is incorporated into the model. This control...
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