Teaching
Intelligent and Autonomous Mobile Robots
Spring 2020
MECH 7020 is a graduate-level introduction to algorithmic and software tools that allow mobile robots to operate autonomously in unknown and dynamic environments taught by Professor Manish Kumar. The course broadly covers methods and tools for three areas of robotics: state estimation, localization and mapping, and motion planning and control. A team of two other students and I pioneered the course curriculum design because it was the first time it would be offered. As the teaching assistant, I created all the programming assignments, hardware checklists, and the final project. I also prepared the lecture materials and taught ROS/Gazebo to the students to enable them to implement the concepts in the class. Finally, I tutored and supervised the students on how to build and control the NVIDIA Jetson Nano robots. Because of COVID, we switch to a simulation-based project which was utilizing EKF-SLAM with AprilTags Landmarks on Turtlebot3 in ROS/Gazebo.
Workshops
Real-Time Automated Vehicle Crash Detection and Reporting System
Role: Presenter at the 21st Annual Pilot Research Project Symposium
According to World Health Organization, the number of deaths caused by road traffic crashes is approximately 1.35 million people around the world each year, and between 20 and 50 million suffer people with non-fatal injuries each year due to vehicular crashes. Delays in detecting and providing care for those involved in a road traffic crash increase the severity of injuries. A faster rescue response has the potential to not only save lives but also result in faster clearing of accidents and lesser congestion. The motivation behind the proposed study is to minimize the response time of the authorities, including first responders and firefighters for restoring the traffic operations after vehicular crashes and in the process save lives.The main objective of this project is to develop a low-cost automated vehicle crash reporting video analytics software which can detect and report vehicular crashes at the traffic intersections.
Autonomous Mobile Robot Localization and Navigation system using camera and inertial measurement unit (IMU) in an indoor environment
Role: Co-Presenter at AIAA Intelligent Systems Workshop, July 2019
I co-presented the preliminary results of our work at the conference. Authors: Kumat Ashwin, Omotuyi Oyindamola, Deshpande A. M., Calabrese Nate, Kumar Manish
Talks
NVIDIA Emerging Chapters Developer Meetup March 21, 2022
Role: Presenter
I was one of the presenters at the developer meetup at NVIDIA GTC, the Conference for the Era of AI and the Metaverse. It was for the developer communities and their members in the NVIDIA Emerging Chapters program led by Amulya Vishwanath. I spoke on my career journey, internship experience with NVIDIA, and shared tips on how to get started on an AI journey.
Laser-Based EKF Localization on TurtleBot3 Robot
Role: Presenter at the 44th Dayton-Cincinnati Aerospace Sciences Symposium. March 2019.
This project presents a technique on the localization of a ground robot using the Extended Kalman Filter (EKF) with the use of a Light Detection and Ranging (Lidar) sensor. The use of EKF in localizing robots has been highly successful when working with small maps for many years. The goal of this project was to design and implement an algorithm which would replicate what has already been done using Python, ROS and Gazebo. This software environment was chosen because of its widespread use in industry and its ability to enable a quick transition between hardware and simulation. The simulation was based on the TurtleBot3 Burger platform. This platform was equipped with a 360 Laser Distance Sensor LDS-01.