Hi, I'm Darshan K T Gowda

Robotics Engineer | Control & Navigation Specialist | ROS Developer | Maker

About Me

Passionate robotics engineer with a Master’s degree and 6+ years of experience across AMRs, drones, underwater, and humanoid robotics. Skilled in ROS2, Python, C++, embedded systems, and AI, with a focus on building intelligent real-world robotic systems.

Education

The National Institute of Engineering, Mysuru, India

MTECH/MS in Industrial Automation and Robotics

Courses: Programming Practical Robots, Kinematics & Dynamics of Robots, Mobile robotics, Optimal Control & Estimation, Computational Methods for Robotics, Hydraulics and pneumatics, PLC, Drives & control system, Foundations of Robotics, Linear Control Systems

Ghousia College of Engineering, India

BE/BTECH in Mechanical Engineering

Courses: Mechatronics, Mechanical Design & Analysis, Michanical Vibration, Automotive electronics, Control Systems, Machine Dynamics, Manufacturing

Skills

Programming

C/C++, Python, Arduino, CUDA Programming

Software Tools

Docker, Dev Containers, Github, VS code, Linux

Robotics - Tools

ROS/ROS2, MoveIt, Gazebo, RViz, OpenCV, PCL

Robotics - Types

AMR, Drones, Arm robots, ROVs

Robotics - Concepts

Path Planning(Global & local planning), SLAM, Kalman Filters(EKF), PID

Sensors

2D/3D Lidars, RGB-D Camera(Zed, Kinect, Realsense), GPS(RTK)

Embedded Systems

Pixhawk, ESP32, Raspberry Pi, Jetson Nano

Projects

Multi-Robot Navigation using RMF and TurtleBot3

Autonomous Navigation using TurtleBot and ROS

Implemented autonomous navigation on a TurtleBot using ROS. Built a 2D occupancy grid map via gmapping, localized using AMCL, and executed autonomous goal-directed navigation avoiding obstacles.

ROS
SLAM
AMCL Localisation
Navigation
Turtlebot3

BlueROV2 Underwater Robot Setup

Configured and deployed the BlueROV2 robot for underwater operation using QGroundControl and Xbox controller. Achieved live video streaming and control, and laid the groundwork for ROS2 integration with future YOLO-based perception tasks.

BlueROV2
QGroundControl
Xbox Controller
ArduSub
Pixhawk
Raspberry Pi
ROS2 (Future)
YOLO Detection (Future)

SITL + Gazebo UAV Simulation

A two-part simulation framework using ArduPilot SITL and Gazebo to develop and test autonomous navigation and flight control of quadrotors without real hardware. Supports mission planning, flight modes, and 3D visualization.

ArduPilot SITL
MAVProxy
Gazebo
Flight Simulation
Mission Planning
Autonomous UAV Control

Pole Detection & Midpoint Calculation

Designed a LiDAR-based navigation system for a robot operating beneath solar panels. Used point cloud filtering to detect poles and calculate midpoints for autonomous mowing.

LiDAR
Point Cloud Filtering
ROS 2
Midpoint Path Planning
Simulation in Gazebo

GPU Virtualization for OpenPose

Demonstrated how GVirtuS virtualizes GPU resources to run the GPU-hungry OpenPose application on lightweight non-GPU edge devices by redirecting CUDA calls to a remote GPU backend.