Theory Of Wing Sections Including A Summary Of Airfoil Data

Concise deep reinforcement learning obstacle avoidance for underactuated unmanned marine vessels

The development of magnetic field sensors for biomedical applications primarily focuses on equivalent magnetic noise reduction or overall design improvement in order to make them smaller and cheaper while keeping the required values of a limit of detection. One of the cutting-edge topics today is the use of magnetic field sensors for applications such as magnetocardiography, magnetotomography, magnetomyography, magnetoneurography, or their application in point-of-care devices. This introductory review focuses on modern magnetic field sensors suitable for biomedicine applications from a physical point of view and provides an overview of recent studies in this field. Types of magnetic field sensors include direct current superconducting quantum interference devices, search coil, fluxgate, magnetoelectric, giant magneto-impedance, anisotropic/giant/tunneling magnetoresistance, optically pumped, cavity optomechanical, Hall effect, magnetoelastic, spin wave interferometry, and those based on the behavior of nitrogen-vacancy centers in the atomic lattice of diamond.

Ultrasensitive Magnetic Field Sensors for Biomedical Applications.

In this paper, a dynamic model of a wheeled mobile robotic (WMR) system with coupled control input is developed, which will increase the complexity of its tracking control with time-varying advance angle. To deal with this problem, a partial reinforcement learning neural network (PRLNN)-based tracking algorithm is proposed for the WMR systems. The main contributions of the PRLNN adaptive tracking control method is that it is the first control method to introduce the PRLNN adaptive control to the WMR system, which determines to solve the WMR tracking control with the time-varying advance angle. The critic neural network (NN) and action NN adaptive laws for the decoupled controllers are designed using the standard gradient-based adaptation method. According to the Lyapunov stability analysis theorem, the uniform ultimate boundedness of all signals in the WMR system can be guaranteed with the design parameters chose properly, and the tracking error converge to a small compact set nearby zero. A numerical simulation is presented to verify the effectiveness of the proposed control algorithm.

Adaptive Partial Reinforcement Learning Neural Network-Based Tracking Control for Wheeled Mobile Robotic Systems

Otolithic afferents with regular resting discharge respond to gravity or low frequency linear accelerations, and we term these the static or sustained otolithic system. However in the otolithic sense organs there is anatomical differentiation across the maculae and corresponding physiological differentiation. A specialized band of receptors called the striola consists of mainly type I receptors whose hair bundles are weakly tethered to the overlying otolithic membrane. The afferent neurons which form calyx synapses on type I striolar receptors have irregular resting discharge and have low thresholds to high frequency (e.g. 500Hz) bone conducted vibration and air conducted sound. High frequency sound and vibration likely causes fluid displacement which deflects the weakly tethered hair bundles of the very fast type I receptors. Irregular vestibular afferents show phase locking, similar to cochlear afferents, up to stimulus frequencies of kilohertz. We term these irregular afferents the transient system signalling dynamic otolithic stimulation. 500Hz vibration preferentially activates the otolith irregular afferents, since regular afferents are not activated at intensities used in clinical testing whereas irregular afferents have low thresholds. We show how this sustained and transient distinction applies at the vestibular nuclei. The two systems have differential response to vibration and sound, to ototoxic antibiotics, to galvanic stimulation and to natural linear acceleration, and such differential sensitivity allows probing of the two systems. 500Hz vibration which selectively activates irregular otolithic afferents results in stimulus-locked eye movements in animals and humans. The preparatory myogenic potentials for these eye movements are measured in the new clinical test of otolith function – ocular vestibular evoked myogenic potentials. We suggest 500Hz vibration may identify the contribution of the transient system to vestibular controlled responses such as vestibulo-ocular, vestibulo-spinal and vestibulo-sympathetic responses. The prospect of particular treatments targeting one or the other of the transient or sustained systems is now being realized in the clinic by the use of intratympanic gentamicin which preferentially attacks type I receptors. We suggest that it is valuable to view vestibular responses by this sustained-transient distinction.

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Sustained and Transient Vestibular Systems: A Physiological Basis for Interpreting Vestibular Function.

Purpose




Autonomous obstacle avoidance is important in unmanned surface vehicle (USV) navigation. Although the result of obstacle detection is often inaccurate because of the inherent errors of LIDAR, conventional methods typically emphasize on a single obstacle-avoidance algorithm and neglect the limitation of sensors and safety in a local region. Conventional methods also fail in seamlessly integrating local and global obstacle avoidance algorithms. This paper aims to present a cooperative manoeuvring approach including both local and global obstacle avoidance.




Design/methodology/approach




The global algorithm used in our USV is the Artificial Potential Field-Ant Colony Optimization (APF-ACO) obstacle-avoidance algorithm, which plans a relative optimal path on the specified electronic map before the cruise of USV. The local algorithm is a multi-layer obstacle-avoidance framework based on a single LIDAR to present an efficient solution to USV path planning in the case of sensor errors and collision risks. When obstacles are within a layer, the USV uses a corresponding obstacle-avoidance algorithm. Then the USV moves towards the global direction according to fuzzy rules in the fuzzy layer.




Findings




The presented method offers a solution for obstacle avoidance in a complex environment. The USV follows the global trajectory planed by the APF-ACO algorithm. While, the USV can bypass current obstacle in the local region based on the multi-layer method effectively. This fact was validated by simulations and field trials.




Originality/value




The method presented in this paper takes advantage of algorithm integration that remedies errors of obstacle detection. Simulation and experiments were also conducted for performance evaluation.

Autonomous obstacle avoidance of an unmanned surface vehicle based on cooperative manoeuvring

People detection and tracking is an essential capability for mobile robots in order to achieve natural human–robot interaction. In this article, a human detection and tracking system is designed an...

https://journals.sagepub.com/doi/pdf/10.1177/1729881416657746

People detection and tracking using RGB-D cameras for mobile robots:

In rectilinear locomotion, snakes propel themselves by extending or contracting parts of the body. It is interesting that some large snakes will lift the activated part of the body during rectilinear motion. We hypothesize that snakes use this unique strategy named “lifting behavior" to improve the performance of rectilinear motion on a rough horizontal surface. The purpose of this paper is to examine our hypothesis by examining whether rectilinear motion benefits from lifting behavior. In this study, we derive equations to estimate the energy consumption of rectilinear motion on a simplified 4-link snake robot model. We consider not only mechanical energy dissipation but also heat energy loss during motion. A criterion of minimum energy loss is used as a candidate for the strategy to show how much lifting behavior improves energy efficiency. Our analysis provides a framework for theoretical analysis of the energy cost of rectilinear locomotion for snakes, which can help biologists to further understand the behaviors of snakes. This study also provides some new insights into rectilinear locomotion.

The influence of lifting behavior on energy efficiency in rectilinear locomotion

With the wide application of large-scale flexible structures in spacecraft, vibration control problems in these structures have become important design issues. The filtered-X least mean square (FXLMS) algorithm is the most popular one in current active vibration control using adaptive filtering. It assumes that the source of interference can be measured and the interference source is considered as the reference signal input to the controller. However, in the actual control system, this assumption is not accurate, because it does not consider the impact of the reference signal on the output feedback signal. In this paper, an adaptive vibration active control algorithm based on an infinite impulse response (IIR) filter structure (FULMS, filtered-U least mean square) is proposed. The algorithm is based on an FXLMS algorithm framework, which replaces the finite impulse response (FIR) filter with an IIR filter. This paper focuses on the structural design of the controller, the process of the FULMS filtering control method, the design of the experimental model object, and the experimental platform construction for the entire control system. The comparison of the FXLMS algorithm with FULMS is theoretically analyzed and experimentally validated. The results show that the FULMS algorithm converges faster and controls better. The design of the FULMS controller is feasible and effective and has greater value in practical applications of aerospace engineering.

https://iopscience.iop.org/article/10.1088/0964-1726/22/8/085008/pdf

Analysis and implementation of a structural vibration control algorithm based on an IIR adaptive filter

With the wide application of robot in unstructured environment, cognizing and understanding environmental information accurately is the key for robots to complete the task. Thus, visual stability problems in these robot control systems have become important design issues. In this paper, to solve the problem of vision instability caused by attitude variation of the robot working under bumpy environment, a bionic eyes system of active compensation for robot visual error is proposed inspired by the binocular VOR. The bionic vision system is developed based on features of oculomotor behaviors and bionic control algorithm of the binocular VOR. According to the behaviors features of eye movement, the bionic eye mechanism is designed by using a 3-DoF spherical parallel mechanism(SPM). Meanwhile, to improve the performance, the mechanism parameters of SPM are optimized by utilizing the worst-case performance index as the optimizing target in required workspace. An adaptive control model of the binocular VOR is established on neural control mechanisms of eye movement, and the model is used as the bionic control algorithm to drive and control the eye mechanism. The results indicate that the model can actively compensate the visual errors from postural changes of robot. Physical robot experiments also show that the system is robust even with bumpy environment.

Hengyu Li

Papers

Autonomous obstacle avoidance of an unmanned surface vehicle based on cooperative manoeuvring

People detection and tracking using RGB-D cameras for mobile robots:

The influence of lifting behavior on energy efficiency in rectilinear locomotion

Analysis and implementation of a structural vibration control algorithm based on an IIR adaptive filter

Design and Control of 3-DoF Spherical Parallel Mechanism Robot Eyes Inspired by the Binocular Vestibule-ocular Reflex