Welcome To My Portfolio
I'm
Name: Vrusahbh Desai
Email: vmdesai@wpi.edu
Phone: +1 (508)-206-0188
Interest: Software Design, Computer Vision, Deep Learning, Electronics
Education
M.S in Robotics Engineering
Worcester Polyrtechnic Institute, MA. (May 2021) 4/4
CGPA
B.E in Electronics Engineering (Minor in
Artificial Intelligence)
D.J.Sanghvi College of Engineering, India. (June 2018) 8.7/10
CGPA
C++ Nanodegree
Udacity (June 2020)
Techincal Skill
Programming Language: C, C++ and Python 95%Interpersonal Skills
Project Management (using Jira) 95%Currently I am working as a Software Engineer at Cognex. I completed my Masters in Robotics Engineering at Worcester Polytechnic Institute, Massachusetts. and my B.E in Electronics Engineering from Dwarkadas J. Sanghvi College of Engineering, Mumbai University. My research interests lie broadly in the fields of Computer Vision, Deep Learning and Path Planning for solving real-world problems.
After completing my undergraduate degree, I had the opportunity to work as a Signal Processing and Control Algorithm Engineer at Earth Energy EV, where I led a team in designing and manufacturing a wiring harness and electronic control unit for an electric motorbike. During my time there, we also designed a Level-2 electric smart charger and worked on an autonomous electric delivery robot. These projects provided me with valuable hands-on experience with software tools such as Atmel Studios, SolidWorks, Rapid Harness, and LTspice, as well as software libraries such as OpenCV and Scikit-Learn.
During my undergraduate studies, I was an active member of Team DJS Racing for two years. DJS Racing is a Formula Student team from D.J.Sanghvi College of Engineering that competes in Formula Bharat, Formula Student Germany, and Formula Student Austria. As the Electronics and Data Acquisition Lead of the team, I developed an industrial-grade Electrical Wiring Loom in collaboration with Spark Minda. Additionally, I designed and implemented a closed-loop Drag Reduction System for the Aerodynamic package that utilized feedback from the Brake Pressure Sensor and Steering Angle position. We also developed a Telemetry system to collect data from various sensors on the car, which was used to improve the car's performance. Despite balancing my regular academic workload, these experiences allowed me to enhance my skills and knowledge in Electronics and Data Acquisition.
My involvement in both professional work and extracurricular activities has instilled in me a profound sense of responsibility and a desire to take on larger roles in the future
Achievements
Consecutive two National Awards for Best Designed Formula Student Car at Formula Bharat held in January 2017 and
January 2018 at Kari Motor Speedway, India.
Overall Second Best Asian
Team at Formula Student Germany held in August 2017 at Hockenheim,Germany.
International Awards for Static Event
Performance (Cost Event) at Formula Student Austria held in July 2018 at Red Bull Ring,
Austria.
To explore my work please select a category
(June 2017 - March 2018)
[ Video
]
[ Report ]
Analyzed forward Kinematics of 3 DOF SARA robotic arm using DH parameters and designed the CAD model on SolidWorks studied the strength of the structure using FEA. Tuned the PID controller of the arm to reach the desired location and LabVIEW was used as backend software.
Language: Embedded C | Platform: SolidWorks, LabVIEW
(July 2019 - June 2019)
[ Report ]
Interfaced Arduino Uno with GY61 accelerometer sensor which has ADXL-335 as a sensing element, that can measure acceleration up to a minimum of +/- 3 g and gives the voltage linearly proportional to the acceleration. According to sensor values, L298N motor driver is used to control all four DC Motors mounted on wheelchair.
Language: C | Platform: Arduino
(January 2017 - April 2017)
[
Report ]
Designed minimum embedded system board using EDA tools like Eagle, which get the X, Y and Z-Axis angles from an inertia sensor (MPU 6050) located on the user’s hand. According to the sensor value a SCARA based pick and place robotic arm is driven.
Language: Embedded C | Platform: Atmel Studios
(August 2016 - October 2016)
[ Report ]
Designed and carried out the circuit simulation of various passive components using LTspice. I was capable to successfully generate 150V surge at primary coil using capacitors as an energy storage bank.
Platform: LTspice
(January 2014 - April 2014)
Germanium Diode was used as a heat-sensing element in the circuit. As the temperature near diode increases the diode reverse resistance drops increasing voltage at the non-inverting terminal of the operational amplifier which in turn on the external speaker and detect fire.
Platform: LTspice
(May 2020 - August 2020) [ Video ] [ Report ]
Designed point-to-point and multi-point PID controller for turtlebot and simulated its performance on
ROS gazebo.
Deployed PID controller on actual turtlebot hardware and compared simulation results with actual
hardware performance.
Language: C++ | Platform: ROS, Gazebo
(February 2020 -May 2020) [ Video ] [ Report ]
Analyzed of two different 3-DoF serial manipulators, specificly cartesian (PPP) & articulated (RRR)
with respect
to different trajectory generation methods like Point-to-Point trajectory, continuous path like circle
or sinusoidal wave trajectory.
Compared energy consumed by the manipulator for different trajectory interpolation methods.
Platform: MATLAB
(February 2020 - May 2020) [ Report ]
Performed 3D object detection on the KITTI dataset with the goal of reduced computation time and
memory.
Experimented with using SqueezeDet in the Frustum PointNet architecture for 2D detection instead of a
fine-tuned Fast R-CNN
Language: Python | Platform: Google Cloud Platform
(February 2020 - May 2020.) [ Video ]
The goal of the project was to implement Real-Time Appearance-Based Mapping of the indoor environment
using RGB-D Camera on turtlebot3.
Successfully generated robust 2D and 3D maps for an unknown environment using Li-DAR, IMU sensors and
RGB-D camera on turtlebot3.
Language: C++ | Platform: ROS,Gazebo
(September 2019 - December 2019) [ Report ]
Implementing an API that identifies the distracted driver and triggers the onboard alarm which helps
to focus on driving. Designed and trained a different multi-class
classification algorithm like SVM, Decision Trees, Random Forests and CNN’s capable of detecting 10
different human
distractions based on driver’s activity with an average accuracy of ~ 92%
Language: Python
(September 2019 - December 2019) [ Video ] [ Report ]
Extracted image feature’s using SHIFT, SURF, Hough Transform, and dynamic thresholding to detect
traffic signal in a frame.
Integrated Deep Neural Network based object detection method YOLOv3 for robust detection and SVM for
status recognition.
Language: Python
(March 2017 - May 2018)
[ Video
]
[
Specifications ]
Improvising on previous designs this season I designed a custom embedded board which serve as a Power Distribution Module for the car, which also has a feature to control the “Paddle Controlled High-Tech Servo Motor” which was used to actuate the clutch. Designed a Data Logger and Telemetry system using Race Capture Pro MK3 which collects data from various sensors on the car and use that data to improvise its performance of the car.
(March 2016 - Feb 2017)
[ Video
]
[
Specifications ]
[
Report ]
Designed an industrial-grade Electrical Wiring Loom which was compatible with Custom programmable Performance Electronics PE3 ECU. Developed Electronic Solenoid Shifter system with ignition interrupts for fast gear shifting. Effectively developed a closed-loop Drag Reduction System for Aerodynamic package which gets the feedback from brake pressure sensor and steering angle position
Capstone Project which utilizes the core concepts from object-oriented programming, memory management, and concurrency. Once the game starts it creates objects, then the game continues to loop through each component and simultaneously grabs input from the user. There are three different levels in which the user can start with Easy, Medium, and Hard.
Built a multithreaded traffic simulator using a real urban map. Each vehicle runs on a separate thread and managed intersections using traffic lights to facilitate traffic flow and avoid collisions. Visualization can be seen on github repository.
Implemented Chatbot using modern C++ memory management techniques such as smart pointers and move semantics. The knowledge base was loaded from a text file, a knowledge graph representation was created in computer memory. After a user query has been sent to the chatbot, the Levenshtein distance is used to identify the most probable answer.
The system monitor shows what’s the current process running on your computer. Processes id, CPU and memory usage, etc. Object-oriented C++ was the backbone to build a Linux system monitor similar to the widely used htop application.
Used OpenStreetMap data and the IO2D visualization library to build a route planner that finds a path between two points on a real-world map using the A-star algorithm.
20
PROJECTS COMPLETED20
TOTAL MONTHS OF EXPERIENCE200
TOTAL HOURS OF6
AWARD WONI had successfully completed the following courses: