An Introduction to Inertial and Visual Sensing
International Journal of Robotics Research
Flying Fast and Low Among Obstacles: Methodology and Experiments
International Journal of Robotics Research
Autonomous Vision-Based Helicopter Flights Through Obstacle Gates
Journal of Intelligent and Robotic Systems
Visual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration
International Journal of Robotics Research
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Cameras and inertial sensors are good candidates to bedeployed together for autonomous vehicle motion estimation,since each can be used to resolve the ambiguities in theestimated motion that results from using the other modalityalone. We present an algorithm that computes optimalvehicle motion estimates by considering all of the measurementsfrom a camera, rate gyro, and accelerometer simultaneously.Such optimal estimates are useful in their ownright, and as a gold standard for the comparison of onlinealgorithms.By comparing the motions estimated using visual and inertialmeasurements, visual measurements only, and inertialmeasurements only against ground truth, we show thatusing image and inertial data together can produce highlyaccurate estimates even when the results produced by eachmodality alone are very poor. Our test datasets include bothconventional and omnidirectional image sequences, and animage sequence with a high percentage of missing data.