The Winner's Circle
Cool projects. Raw talent. The right tools. With these ingredients student competition teams are winning competitions worldwide and shaping the future of automotive design, aerospace engineering, robotics, and many other technical fields
1st Place – Single-Occupant Vehicle - Formula Sun Grand Prix (FSGP) 2019
With the help of MATLAB, the team monitored the battery’s state by parsing through the CAN bus data. They also compared the predicted weather and current weather to determine the optimal driving speed. This was the key to the team’s race strategy.
Winning FSAE Lincoln 2019 - FSAE Michigan, FSAE North, FSAE Lincoln
The FPM19 (Formule Polytechnique Montréal) was developed from the past iteration of the car based on a full car model built in Simulink with the use of Simscape Multibody and other libraries from Simulink. This tool was used to get laptime simulation, load analysis of the suspension, transient responses of the vehicle and many other parameters. This allowed the team to compare different car modifications and implement the best option for the 2019 iteration.
1st Overall, 1st in Engineering Design, 1st in Acceleration, 2nd in Skidpad, 3rd in Energy Efficiency, 3rd in Sales Presentation - Formula SAE Electric (Lincoln, Nebraska) 2019
With MATLAB, the team was able to generate a point-mass lap sim that determines all their design targets. With Simulink, they were able to generate a Battery Model and a State of Charge Estimator with Kalman Filtering. They were also able to generate a Torque Controller that includes Regenerative Braking and Traction Control.
Liaoning University of Technology
2nd Place - Formula Student China 2018
Wonder Electric Formula Racing Team of Liaoning University of Technology won 2nd place in the Formula Student China 2018 final. The team used a complete verification tool chain, including Simulink Requirement, Simulink Check, Simulink Test, Simulink Coverage, and Simulink Design Verifier to fully verify the algorithm model according to industry product development process, which greatly improved their development efficiency and software reliability in the competition.
1st Overall, Endurance award, CAE award and Sales award - BAJA SAEINDIA 2019, Indore
The team used Simulink to simulate their range for the endurance race and optimize their performance. They also used MATLAB for all important steering and brake calculations.
Rashtreeya Vidyalaya College of Engineering
2nd overall in mbaja at BAJA SAEINDIA 2019, IIT Ropar
Team Helios Racing of RV College of Engineering placed 2nd overall at BAJA SAE INDIA, IIT Ropar. They used MATLAB to obtain the primary and secondary Ramp profiles of their custom continuously variable transmission. These ramp profiles serve as the part against which rollers roll to vary the side force acting on the belt. The belt transfers power from the primary pulley to the secondary pulley.
National University of Ireland Galway
Technical Innovation Award - Shell Eco-marathon Europe 2018
The team’s goal is to complete a 14.5-km course at an average speed of at least 25 km/h, using minimum energy. In order to derive an optimal racing strategy, a shortest path algorithm was written in MATLAB to work in conjunction with a Simulink vehicle model. This guided the designers and drivers to select the optimal drivetrain configuration and acceleration zones to be used on the given track.
University of Thessaly
2nd Place in Class 2 - Formula Student UK 2018
After taking 1st place in Design Event and 3rd in Business Plan Presentation, Centaurus Racing Team from University of Thessaly managed to claim 2nd place overall in Class 2 in IMechE Formula Student 2018. They used MATLAB for tire data analysis, dynamic analysis, and design optimization of a half-shaft.
1st Place - Student Formula Japan 2018
Osaka-Univ. Formula RAcing Club won first prize in the Student Formula Japan 2018 competition. They made a four-wheel car model using Simulink and simulated the car’s stability at different steering angles. They also determined the optimal length of the wheelbase, so that the car would remain stable while running on a skip pad for five seconds.
1st Place Combustion and 3rd Place Overall - Formula Student UK 2018
Monash Motorsport from Monash University in Melbourne, Australia won the Formula Student UK 2018 competition with their combustion car and came in third place overall with their first ever electric car. They used MATLAB for vehicle dynamics and lap time simulation in order to inform both conceptual design decisions and tuning. MATLAB and Simulink were also used extensively in powertrain development and troubleshooting.
Pimpri Chinchwad College of Engineering
1st Place - SUPRA SAEINDIA 2018
Team Kratos Racing from PCCOE, Pune stole the show at SUPRA SAEINDIA 2018 when they were not only declared overall winners, but also secured first place in CAE, Design, Business Plan, Skidpad, Autocross, and Engineering Excellence. It was indeed a great victory as the team won seven out of the total 10 awards this year. They also celebrated a remarkable triumph over being champions for the third time in a row. The team extensively used MATLAB and Simulink for tire modeling, suspension modeling, and Stateflow modeling, which helped in detailed and efficient designing of the vehicle.
University of Toronto
1st Place - AutoDrive Challenge Year 1 2018
Team auToronto from University of Toronto won the Year 1 finals of the SAE AutoDrive Challenge with their autonomous Chevrolet Bolt called Zeus. They used Automated Driving Toolbox for automated ground truth labelling. They also used Robotics System Toolbox to hook into their sensors and vehicle controls from within MATLAB.
Technical University of Munich
1st Place - SpaceX Hyperloop Pod 2018
After their victories in recent years, team WARR Hyperloop from the Technical University of Munich won the SpaceX Hyperloop Pod Competition for the third time in a row by building the fastest prototype in the race. The team used MATLAB and Simulink to optimize the design of the propulsion unit and to determine the optimal operation parameters.
1st Place MathWorks Simulation Award - Formula Student China 2017
The Tongji DIAN Racing team won the 1st place MathWorks award for vehicle dynamic modeling in FSC 2017. Simulink was used for control algorithm design including traction control, torque vectoring, and energy reoccupation. The vehicle model, suspension system, and battery model were also built with Simulink and Simscape Driveline for system analysis and optimization.
1st Place - Formula Student UK 2017
The Cardiff Racing team has been crowned the 1st place winner of Formula Student UK from the UK. They used MATLAB throughout their design for tire data analysis and general data analysis. Cardiff Racing were also awarded the Exxon Mobil award for best innovation for their exhaust which had been designed recording the sound of the engine and using MATLAB to perform a Fast Fourier Transforms (FFTs) giving a visual representation of the frequencies produced.
This was also the first year the team used Simscape Multibody to analyse suspension behaviour in their car.
Technical University of Munich
2nd Place - Shell Eco-Marathon Europe 2018
TUfast Eco Team from TU Munich succeeded in the new autonomous category. They used MATLAB and Simulink for crucial parts of the design of their car called muc018, “be it to prepare or analyze data, generate code for the planning system, write full ROS nodes in Simulink or even generate code for the GPU,” says Maximilian Mühlbauer, their 2018 head of autonomous driving.
University of Stuttgart
1st Place - Formula Student Spain 2018
GreenTeam from University of Stuttgart, who uses Speedgoat Baseline as their main ECU and is the only team to do so in Formula Student worldwide, won Formula Student Spain 2018 after scoring first at FS Germany and Hungary in August 2017. Formula Student Spain 2018 is remarkable because the partner team Rennteam also won their category. Find more about GreenTeam‘s fast and robust development approach using Simulink Real-Time in the user story from Speedgoat.
1st Place - Formula Student Germany 2018 - Driverless and Electric Category
The team used Simulink to design the vehicle dynamics controllers and MATLAB to develop optimal trajectory planning for their driverless car.
Eindhoven University of Technology
1st Place - Soccer Middle Size League RoboCup 2019
Tech United, the robot soccer team from Eindhoven University of Technology, won 1st Place in the RoboCup Soccer Middle Size League 2019 in Sydney, Australia. The team uses MATLAB and Simulink to develop and generate real-time control software for their robot soccer players. This allows the team to rapidly develop complex software, ranging from vision to real-time motion control to strategy software.
Technische Universität Graz
2nd Place - Logistics League RoboCup 2019
Team GRIPS achieved 2nd place at the RoboCup Logistics League competition 2019 in Sydney. MATLAB and Simulink were used in the parameter tuning process for several control loops. The team plans to integrate MATLAB even more in the software stack by connecting to the Robot Operating System (ROS). This will enable the team to conveniently implement more sophisticated control algorithms.
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
2nd Place - Soccer Small Size League RoboCup 2019
ER-Force is a RoboCup Soccer Small Size League team that came in second place in this year’s international event in Sydney, Australia. They used MATLAB to develop, simulate, and optimize their motion control systems for their autonomous soccer robots.
Efficient and precise motor control is crucial in the competitive RoboCup environment and MATLAB has allowed them to keep up with the competition despite using smaller (and therefore less powerful) motors.
Shattuck Public School
2nd Place BEST Award – Frontier Trails BEST Regional Robotics Championship 2018
The team at Shattuck Public School used Simulink to provide a simulation of their robot structures to help them design and build an effective robot. This year’s goal was to build a robot that might help clean up the oceans, and it was an exciting challenge.
Eastwood/Cornerstone Schools, Montgomery, AL
3rd Place Game Winners – South’s BEST Regional Robotics Championship 2018
Gears, Inc. Robotics team, from Eastwood/Cornerstone Schools, won the Simulink Design Award at the South’s BEST Regional Robotics Championship. They used Simulink and Stateflow to program their robot’s drive and control functions, allowing it to collect trash from a simulated ocean environment. The award was given based on the design and sophistication of the Simulink model, as well as the performance of their robot.
Bumblebee Autonomous Systems; National University of Singapore
1st Place – Maritime RobotX Challenge 2018
Team Bumblebee of National University of Singapore were crowned champions at the Maritime RobotX Challenge 2018, where they deployed an integrated Autonomous Surface Vessel – Autonomous Underwater Vehicle system for the competition. MATLAB was used to analyze underwater acoustic signals, model signal channel conditions, and evaluate and verify acoustic localization algorithms that utilized the Signal Processing and Phased Array System Toolboxes. C and HDL code were also generated and implemented on the system.
Universiti Sains Malaysia
1st Place - Innovate Malaysia Design Competition 2018
Team MY322 designed a distributed cooperative synchronization between master and slave units where both of the robot arms are connected over a network. The control signal is shared amongst them as well as the implementation of a robust observer, which uses sliding mode observer theory. MATLAB and Simulink support package for Arduino as well as Simulink Coder have been used to control the robot arms in synchronized motion and the fault is introduced via software by using Band-Limited White Noise block in MATLAB/Simulink. The team can set the value of noisy signal differently to see the performance of this robust observer.
Universiti Kebangsaan Malaysia
3rd Place - Innovate Malaysia Design Competition 2018
Team MY144 developed a smart and responsive blind with fuzzy logic as a main decision module. The fuzzy logic controls the length and angle of the blind and the LED brightness responds to any variation in thermal comfort parameters. The response is governed by the fuzzy inference system (FIS) and the membership function, namely the fuzzy controller. This system is developed using Fuzzy Logic Toolbox and MATLAB and Simulink support package for Arduino. The data is uploaded to the cloud via ThingSpeak Support Toolbox in order to incorporate the model with the IoT network system. The user can switch on or off the fuzzy controller and can monitor the thermal comfort parameters via a mobile app.
University of Bonn
1st Place - Main Competition, Drop-In Challenge, and Technical Challenge - RoboCup AdultSize Humanoid League 2018
Team NimbRo is one of the most successful teams in the history of the RoboCup Humanoid League, having won many first-place trophies and awards over the years, including 12 in only the last three years. They used MATLAB for the prototyping, visualization, evaluation, and testing of countless algorithms throughout their entire codebase. This includes the design of gait algorithms, dynamic models, numerical methods, soccer behaviors, and much more.
ROBOMOD; Genesis Global School
1st Place - RoboCup@Home Education (High School) 2018
The purpose of RoboCup@Home Education is to familiarize new teams with service robot development and to propel them to participate in RoboCup@Home Major league competitions. Team Nalanda from India used MATLAB for image processing and navigation, which helped them become the only team to complete the restaurant task across the University and High School categories.
2nd Place – OnStage Secondary – RoboCup German Open 2018
2nd Place – OnStage Advanced – European RoboCupJunior Championship 2018
The Evolution Bots won 2nd place in the OnStage category at both the RoboCup German Open and the European RoboCupJunior Championship. The team used MATLAB and Simulink to develop a smart home robot called Dobby, who could perform cleaning and entertainment tasks by working with visual recognition and voice control. Stateflow offered an easy way to switch from one state to another. Dobby is based on Raspberry Pi, which is supported by the Simulink support package.
U V Patel College of Engineering, Ganpat University
1st Place - Best Usage of MATLAB and Simulink - Robocon India 2018
MATLAB helped the team develop a digital image processing algorithm to detect shuttlecock. Simulink helped them develop an algorithm for autonomous and manual robots, and they were able to program the robots with the help of Stateflow.
Technische Hochschule Nürnberg Georg Simon Ohm
1st Place - RoboCup@Work - RoboCup Finals 2018
1st Place – RoboCupRescue and RoboCup@Work – RoboCup German Open 2018
Team AutonOHM from Technische Hochschule Nürnberg Georg Simon Ohm participated in both the Rescue and @Work leagues of RoboCup. They won first place in both leagues at the 2018 German Open event and went on to win first place in the RoboCup@Work League at the RoboCup Finals 2018. The Rescue team used MATLAB to simulate the manipulator for their mobile robot. They also generated C code from their MATLAB algorithms and exported it to their robot.
Richardson High School, Richardson, TX, USA
1st Place - Rose-Hulman Institute of Technology Autonomous Vehicle Challenge 2018
The Rose-Hulman Autonomous Vehicle Challenge is a competition for high school students to build and program a model vehicle to navigate various tracks as fast as possible. Students from Richardson High School in Richardson, Texas won first place at the 2018 Rose-Hulman Autonomous Vehicle Challenge out of 47 teams. This is their second first-place win in a row.
Princeton International School of Mathematics and Science (PRISMS)
Co-champion - Zero Robotics High School Tournament 2017
Held aboard the International Space Station and refereed by astronauts Joe Acaba (United States) and Alexander Misurkin (Russia), the PRISMS Zero Robotics club won co-champion honors in the 2017 Zero Robotics High School Tournament, whose sponsors included MIT, NASA, ESA, and Roscosmos. The PRISMS team used MATLAB to construct and optimize the control algorithm for the SPHERES satellites. Using MATLAB enabled an enhanced satellite stability, a robust kinematic performance, and a superior realization of game strategy, which included topographic mapping and hazard avoidance.
Universiti Teknikal Malaysia Melaka (UTeM)
Consolation Prize - MathWorks Track -Innovate Malaysia Design Competition 2017
The team from the Mechatronics Department, Faculty of Electrical Engineering developed an autonomous underwater vehicle (AUV) with depth control. The AUV was submerged accurately for the desired depth because of the pressure sensor, which was able to continuously send depth data to the controller. The AUV was modeled using System Identification Toolbox to yield the AUV model based on open-loop experiments for depth control. Then, the team used MATLAB and Simulink to simulate and verify the control algorithm. The controllers used in this project included on-off, proportional integral derivative (PID) and Fuzzy Logic Controller.
1st Place - RoboNation's RoboSub 2017
Cornell University’s Autonomous Underwater Vehicle team took home their seventh world championship win and 1st place in static judging at RoboNations’s RoboSub competition in July 2017. The development of their two winning vehicles, Artemis and Apollo, used MATLAB and Simulink to develop a model-based controller, analyze acoustic data, and run mechanical simulations.
Wrocław University of Science and Technology
2nd Place - Red Eagle Contest 2018
MATLAB was used to create a trajectory plan of the Martian lander's flight around the Mars with the influence of Phobos and Deimos. The challenge was also to obtain flight parameters during aerodynamic braking when entering the atmosphere.
Université de Sherbrooke
1st Place - AUVSI's Student Unmanned Aerial Systems 2018
VAMUdeS (Véhicule Aérien Miniature de l’Université de Sherbrooke) is a student group from Québec, Canada, who specializes in autonomous unmanned aircrafts. The team won the AUVSI SUAS Competition for the last three years in a row, and also brought back the Cyber Security Award from the judges this year. VAMUdeS uses MATLAB and Simulink to prevent collisions with virtual obstacles during flight, isolate vibrations on the drone, and improve the accuracy of the different trajectories.
1st Place - AIAA Design/Build/Fly 2018
Clarkson AIAA from Clarkson University used MATLAB to perform sensitivity analysis, enabling the team to optimize their design to score maximum points, select airfoils, and perform aerodynamic calculations. They also used MATLAB to interface with a test rig to map out performance characteristics of propulsion systems and perform data analysis to choose the most appropriate system.
2nd Place - AUVSI's Student Unmanned Aerial Systems 2017
CUAir is an undergraduate project team from Cornell University that develops an autonomous unmanned aircraft that is capable of takeoff, landing, waypoint navigation, and object recognition and classification. CUAir recently placed 2nd internationally (1st in the US) overall and won the Best Technical Design Award in the AUVSI SUAS Competition against more than 50 different teams from across the world, including countries like India, Canada, and Israel. The team uses MATLAB to aid in the design and analysis of their various aircraft.
Israel Institute of Technology
2nd Place - Student Unmanned Aerial Systems 2015
SUAS 2015 competition 2nd place finisher, Israel Institute of Technology, creates a MATLAB obstacle avoidance simulation for their flight vehicle.
Universiti Teknologi Malaysia
2nd Place - Innovate Malaysia Design Competition 2018
First runner up, team MY115 developed a computer vision solution to estimate the level of myopia using the distance between a camera lens and a reference object. From real-time image acquisition, region of interest is extracted using color segmentation. Detection algorithms use the intrinsic parameter of the camera to perform pixel operation and apply triangle similarities. Distance can be computed with less than 2% maximum error after proper calibration. To overcome the stability issue due to surroundings, a GUI with calibrated model parameters is created. MATLAB analysis is done on the data stored on ThingSpeak to remove redundant and useless data pairs. The clean data is gathered by a mobile app with a data visualizer.
University of Manchester
Best Model - iGEM 2016
iGEM 2016 competition Best Model winner, Team Manchester, from the University of Manchester implements an ensemble modelling approach using MATLAB to improve the design of their ethanol biosensor patch.
University of Sydney
2nd Place - iGEM 2016
iGEM 2016 competition first runner-up, Team Sydney Australia from the University of Sydney, engineered bacteria in order to create an ethylene biosensor as a new and practical way of determining ethylene levels in fruits, which is a marker for fruit ripening process. The team used MATLAB and SimBiology to develop a gene regulation pathway model of their ethylene biosensor.
3rd Place - PhysioNet Challenge
PhysioNet/CinC 2016 Challenge 3rd place team, from Cambridge University, uses MATLAB to design a neural network capable of classifying recordings of patients' heart sounds as normal or abnormal.
Universiti Tunku Abdul Rahman
1st Place - MathWorks Track - Innovate Malaysia Design Competition 2017
The Universiti Tunku Abdul Rahman (UTAR) Photonics Research team is carrying out a study on the fibre laser output power modulation by using acoustic emission to target pipeline leakages. The motivation behind this project is to provide a cheaper alternative to the existing pipeline leakage detection techniques in the market and to counter the increasing percentage of Non-revenue water (NRW) in Malaysia. This project uses MATLAB to control instruments to collect pipeline leakage signatures, process the data, and estimate and locate leaks on pipelines.
University Sains Malaysia
3rd Place - MathWorks Track - Innovate Malaysia Design Competition 2017
The second runner-up from the Innovate Malaysia 2017 competition, University Sains Malaysia, designed and developed a machine vision solution to identify the species of adult butterflies according to the database and without catching them. Image Processing Toolbox, Computer Vision Toolbox, Deep Learning Toolbox, and the Android support package from Simulink were used to build the automatic butterfly identification system.
Team B044 (China)
MATLAB Innovation Award - Contemporary Undergraduate Mathematical Contest in Modeling 2016
31,199 teams and over 93,000 students participated in the CUMCM contest in 2016. MathWorks sponsored the MATLAB Innovation Award. Undergraduate team B044 won the award and used MATLAB to do mathematical modeling, numerical simulation, data visualization, and optimization.
1st Place - AES MATLAB Plugin Student Competition and Showcase 2018
Using Audio Toolbox, Silvin Willemsen from Aalborg University won the Gold Award in the first ever AES MATLAB Plugin Student Competition and Showcase. His submission “Extended Virtual Analog Plate Reverb” simulates an audio effect greatly used by Pink Floyd and the Beatles in the fifties and sixties and makes physically fixed parameters—such as length and width of the plate and microphone positions—dynamic in real time.
University of New South Wales Sydney
1st Place - IEEE Signal Processing Cup 2017
Team Beats on the Barbie from the University of New South Wales Sydney took 1st place in the IEEE Signal Processing Cup 2017. Forty universities participated in this global student competition to implement a real-time beat tracker. MATLAB played a key role in the prototyping and testing of the real-time beat tracking algorithm and guided the embedded system development.
Université Laval – Faculté des sciences de l’administration
1st Place overall – Rotman International Trading Competition 2019
Our team used MATLAB to systematize our trading strategy for the options trading case and for the algorithmic trading case. It allowed us to trade efficiently, minimize trading errors and maximize profits in each heat.
1st Place – MATLAB Volatility Trading Case, Rotman International Trading Competition 2018
The team used MATLAB to build a fully automated trading algorithm that can adapt to dynamic market conditions and capitalize on arbitrage opportunities while managing risk exposures