Volume 3: Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control System 2018
DOI: 10.1115/dscc2018-9079
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A Dynamics-Agnostic State Estimator for Unmanned Aerial Vehicles Using Ultra-Wideband Radios

Abstract: We present a state estimator for a UAV operating in an environment equipped with ultra-wideband radio beacons. The beacons allow the UAV to measure distances to known positions in the world. The estimator additionally uses the vehicle’s rate gyroscope and accelerometer, and crucially does not rely on any knowledge of the vehicle’s dynamic properties (e.g. mass, mass moment of inertia, aerodynamic properties). This makes the estimator especially useful in situations where the exact system parameters are unknown… Show more

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Cited by 6 publications
(6 citation statements)
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“…The experiment utilized 5 UWB beacons and the drone is set to execute the two mentioned tasks. Results from the experimentation suggested that there was a relatively large error in the position tracking [11].…”
Section: Previous Workmentioning
confidence: 99%
“…The experiment utilized 5 UWB beacons and the drone is set to execute the two mentioned tasks. Results from the experimentation suggested that there was a relatively large error in the position tracking [11].…”
Section: Previous Workmentioning
confidence: 99%
“…So the states that we are interested in are s E QF , ṡE QF , R EQ . We follow the approach shown in [15] to derive the prediction and measurement update steps.…”
Section: Relative State Estimationmentioning
confidence: 99%
“…A common leisure application for UAV swarms is the frequently witnessed light shows that utilize drones as a green alternative to fireworks. As the number of potential applications of Swarm UAV increases, a significant effort in developing efficient control systems to aid in maneuvering multiple UAVs, while requiring the user to remotely control at most a single drone becomes more and more necessary [6][7][8][9][10]. A critical factor in the control system for swarm implementation is its localization system.…”
Section: Introductionmentioning
confidence: 99%