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... Figure 3a., is a type of sensor for measuring flexion. As the sensor is bent or flexed, the top resistive layer and bottom digitating layer changes the resistance value of the sensor (Raol & Gopal, 2016). The advantage of using Flexible bend sensors for measuring finger ROM is that they are thin, lightweight, easily accessible, and low-cost. ...
Lane changing is one of the crucial tasks for an autonomous vehicle to avoid an obstacle. This task can be performed by controlling the throttle, brake, and steering actuators appropriately based on the analysis of the vehicle’s surroundings. The problem with lane changing is that the control strategy is too complex and needs a high processor for real-time data analysis. In addition, lane changing involves high-level control for vehicle trajectory and low-level control for controlling the steering actuator. This study proposed a well-known method, namely Model Predictive Control (MPC), to determine the vehicle’s lateral position and yaw angle during lane changing maneuver. The optimum steering angle command can control the steer-by-wire (SBW) system from the lateral position and yaw angle in MPC. The Proportional-Integral-Derivative (PID) controller is implemented to control the steering wheel angle in the SBW’s system. Then, the SBW system will turn the wheel of the vehicle plant. From the simulation result, the PID controller can converge the error although the vehicle’s speed is increasing. The result shows that the mean absolute error (MAE) of the SBW system decreases slightly from 0.0115 to 0.0079 as the speed increase from 16 to 41 km/h. From this study, it can be concluded that the MPC and PID controllers can control the vehicle’s trajectory during lane changing by calculating an optimum lateral motion and yaw angle to provide an optimum steering angle for the vehicle to change lanes successfully.KeywordsSteer-by-wire (SBW)Model Predictive Control (MPC)PID controlLane changingAutonomous vehicle
This paper presents HAMSTER, the HeAlthy, Mobility and Security based data communication archiTEctuRe. HAMSTER is designed for Unmanned Vehicles and addresses mainly three types of communications: machine-to-machine, machine-to-infrastructure and internal machine communications. It is divided into three main versions: Flying HAMSTER (for aerial systems), Running HAMSTER (for terrestrial systems) and Swimming HAMSTER (for aquatic systems). Every version of such architecture is also equipped with Sphere and Nimble. Sphere deals with Safety & Security aspects regarding communication, components “health” and modules authentication. Nimble is aimed at increasing the overall mobility in such scenarios, strongly actuating with inherent communications of each application field. This paper details every aspect of HAMSTER and presents, as a plus at the end, two case studies: the first one consists of an evaluation of five communications schemes for internal communications in airplanes; the second one is a cryptographic evaluation of two Elliptic Curve Cryptography algorithms.
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