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Mohamed Fazil

"Let us make this world a better place  with Robots"

My technical experiences and awareness have been around the fields of Assistive technology, Robotics, Prototyping concepts and Deep Learning research. Beyond tech realm, I am passionate of travel and landscape photography.

My Bio

I have always been curious about unique tech applications and uncovering their potential.
 

In 2022, I started working as Robotics Engineer at Hello Robot Inc., dedicated to developing the innovative mobile robot platform 'Stretch.' This is a low-cost, lightweight mobile manipulator designed for safe human interaction and home use. 


In 2021, I earned my Masters in Robotics from the University at Buffalo, US. I served as a Lab Tutor at the Digital Manufacturing Lab, providing advanced 3DP prototyping services and built reverse engineering courses for junior students. Simultaneously, I worked on deep learning research projects in the biomechanics field with motion capture tech, prosthesis controls, and VR at the Assistive Wearable Robotics Lab (AWEAR).

In 2019, I graduated with Bachelors in Mechanical Engineering from Vellore Institute of Technology, India. My experiences span mechanical design, mechatronics, fabrication, computer vision, and tech workshops. I'm proud to have won the University-level Best Project Award for two consecutive years.

STRETCH_MITSKI_MOHAMMED_01.jpg

Hello Robot's Stretch 2 (2022)

(credits: Hello Robot/Julian Mehu)

My Significant Works

Autonomous Ground Vehicle with 3D Perception for Mapping / Multi-Object Pose Tracking

Tracked Differential Drive Robot + Jetson Nano + Realsense D435i + 3-DOF Manipulator

Built a ground robot for environment exploration, a 3-DOF manipulator with Realsense D435i RGB-D camera mounted on a Tracked differential drive mobile Robot fully controlled with ROS using Jetson Nano board. The Robot uses EKF localization fusing the wheel odometry with IMU(MPU6050) for state estimation. Real-Time Appearance based mapping (RTAB-Map) is used for building 3D Space/2D grid maps and localization. Scripted a ROS Multi-Object Tracker node that projects objects in 3D space and broadcasts it to the main TF tree. Built an organized repo of ROS packages for the Robot’s Configuration, Control, Perception and Navigation

3-DOF Desktop Robot for Autonomous Object Tracking in 3D space

3-DOF Manipulator + Intel RealSense D435i + ROS (GitHub)

Adding 3D perception applications to a desktop 3-DOF robot initially designed to mimic the human head’s dexterity. This is a ROS package for Intel realsense D435i with a 3-DOF Manipulator robot that can be used for Indoor Mapping and localization of objects in the world frame with an added advantage of the robot's dexterity. The 3-DOF Manipulator is a self-built custom robot where the URDF with the depth sensor is included. The package covers the Rosserial communication with Arduino nodes to control the robot's Joint States and PCL pipelines required for autonomous mapping/Localization/Tracking of the objects in real-time.

Smart Rollator with Rocker Bogie Suspension and IMU-Linear Actuators based weight distribution control 

University Award Project, Mechanical Engineering Capstone Project (2019)

An advanced rollator(wheel walker) for Elderly and disabled people will help them walk on any obstacle-filled ground, go uphill and down the hill, and climb steps. Uses Rocker Bogie suspension design with linear actuators modifying the user's weight distribution over the rollator in different terrains. Developed unique mechanical design, a mechatronic system consists of linear actuators, Arduino Mega board, BLDC motors with feedback control, and IoT connectivity that can always be relied upon by the elderly. I am now looking forward to developing it as a Product.

Robotic Prosthesis Researcher - Deep Learning, Motion Capture, EMG, Virtual Reality

Researcher at Assistive Wearable Robotics Lab, UB (AWEAR)

I finished my Master's research project on the title "Deep Learning approach to Robotic Prosthetic Wrist Control using EMG signals" under Professor Dr. Jiyeon Kang in Assistive Wearable Robotics Lab (AWEAR), where I designed experiments, collected forearm EMG signals, did 3D reconstruction from Motion capture system and applied Convolutional Neural Networks to predict angular velocities and classify wrist movements that can be implemented in a realtime controller. Previously worked on Myoware based prosthetic hook which involves EMG Signals, Imu Data, 3D reconstructions and kinematics, Euler Angles calculation of rigid body segments, develop Virtual Reality simulation in Mujoco physics engine, and Vicon Motion Capture System.

ROS Autonomous SLAM with Rapidly Exploring Random Tree (RRT)

Mobile Robotics and Lidar Perception (GitHub)

Developed a ROS package for Autonomous environment exploration using SLAM in a Gazebo environment which uses a Laser Range sensor to construct a real-world map at the same dynamically using Rapidly Exploring Random Tree algorithm. The robot uses ROS Navigation stack and RVIZ to visualize the perception of the robot in the environment. My Medium Story of this Project.