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Range-Based Navigation Algorithms for Marine Applications
Published in Chao Gao, Guorong Zhao, Hassen Fourati, Cooperative Localization and Navigation, 2019
David Moreno-Salinas, Naveen Crasta, António M. Pascoal, Joaquín Aranda
We now discuss the results of field tests performed using two Medusa-class AMVs (see Figure 18.13).* Each vehicle has two side thrusters, which can be independently controlled to impart longitudinal and rotational motions about the {zℐ}-axis and two vertical thrusters for depth control. In addition, the vehicles are equipped with attitude and heading reference systems (AHRS) that provide measurement of body orientation and body fixed-angular velocity for control purposes. Each vehicle carries an acoustic Blueprint Seatrac data modem and ranging unit* that is used for communications and range measurements. During the tests, we operated two Medusa vehicles: one of them was used as a target operating at a constant depth underwater, while the other was used as a tracker operating at the surface (equipped with GPS), while interrogating the target. Starting from an unknown initial position, the target executed a lawnmowing motion with a constant body-speed and performed dead reckoning navigation using a DVL and the AHRS. In the tests, for the sake of simplicity, the tracker had access not only to the range to the target but also to the velocity vector of the latter (communicated via the acoustic communications channel) every 1.5 [s]. However, we remark that we can relax this requirement. The target parameters are summarized in Table 18.5.
Is machine learning and automatic classification of swimming data what unlocks the power of inertial measurement units in swimming?
Published in Journal of Sports Sciences, 2021
Matthew T.O. Worsey, Rebecca Pahl, Hugo G. Espinosa, Jonathan B. Shepherd, David V. Thiel
With a single IMUs attached to the torso, much of the limb movement must be inferred. With a single IMUs attached to the wrist, much of the torso and the opposing limb movements must be inferred. The challenge therefore is to determine accurately the body movements from sensor movement. The sensor data is more complex to interpret as acceleration is the double differential of displacement/position, the gyroscope provides angular rotation, and the magnetometer provides information about direction. The acceleration measures include both the static earth component and the dynamic movement components, which cannot readily be distinguished numerically. Clearly, this requires more information than a relatively simple transform from linear acceleration to relative position (Stamm et al., 2013; Worsey et al., 2018). The Attitude and Heading Reference System (AHRS) (Madgwick et al., 2011) is a commonly used data fusion algorithm based on the 9 IMU measurements (3 linear acceleration, 3 angular rotation and 3 axis magnetometer) to determine absolute orientation and movement in space. There are unpublished reports that the movement through the water can distort the magnetometer readings used in AHRS calculations, however.