matlab and simulink mobile devices challenge -凯发k8网页登录

mathworks announces the winners of the 2017 mobile devices challenge. congratulations to the winners and thanks to all those who entered.

 

1st place

matlab mobile floor racing

boris notkin - far eastern federal university

this project demonstrates a racing game that was developed using matlab. in this game, players control racecars that are projected onto a track on the floor mat screen. they use their mobile devices to control these cars that move around the track. to make the game realistic they –

  1. used complicated mathematical equations that govern the physics involved in race cars
  2. processed and used real engine sounds
  3. used stateflow charts to program the logic

the information exchange between players’ mobile devices and floor mat screen is handled by the instrument control toolbox and android/ios support packages from matlab and simulink.

 

2nd place

management of arm robot via android

sasha mymrikov - donetsk national technical university

this video shows how you can control a robotic arm using an android device. first, a simulation model of the real-world robotic arm is used to analyze and visualize the 3-d movements of different joints on the arm. after designing the control logic in simulation, the model is connected to the actual robotic arm. this allows the manipulation of the robotic arm in real-time using the simulink model. then using the simulink support package for android devices, the inputs to the simulink model are replaced by an android smartphone. this enables the user to control the robotic arm both in simulation and real-time using the smartphone. finally, using the gyroscope sensors on their phone the motion of the robotic arm is controlled by rotating the phone in various directions.

 

3rd place

gps tracking of a 550bhp all electric race car using #matlab4mobile

jesper van wordragen - eindhoven university of technology

this team set out to create a low cost alternative to expensive systems that provides real-time position values and tracks the speed of your vehicle. the app that they developed using mobile phone and matlab displays plots for gps data, speed and acceleration reliably in different settings. to highlight the effectiveness of the system they track the speed and position of a bicycle in their university and an all electric race car running in an actual race track. they determine the position by parsing mobile sensor data and performing mathematical computations before plotting them on the app. the app also allows you to save the logged data which can later help them understand the performance and in the case of the electric race car to detect fault points in the event of an accident.

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