Discover @basavarajnavalgund Open Source projects

Basavaraj Navalgund (@basavarajnavalgund)

basavarajnavalgund

Stars
75
Global Rank 255,003 (Top 9 %)
Followers 12
Registered over 6 years ago
Most used languages

C++
75.0 %

CMake 8.3 %

HTML
8.3 %

Jupyter Notebook
8.3 %
Location 🇮🇳 India
Country Total Rank 9,601
Country Ranking

CMake 66

C++
921

Odometry-IMU-GPS-Fusion

Sensor fusion-based localization using robot-localization package

hector-quadrotor

Hector Quadrotor works for both ROS melodic and ROS kinetic

vehicle-localization

Implemented a C++ particle filter for real-time vehicle localization with only current visual observations and a map.

Workplace-Service-Robot

Autonomous Mobile Robot (AMR), a holonomic drive with 4 mecanum-wheels. It autonomously maps an environment, localizes itself, and navigate to pick-up and drop-off objects in a simulated environment.

path_planning

Implemented a simple real-time path planner in C++ to navigate a car around a simulated highway scenario

particle_filter

tracking-with-Extended-Kalman-Filter

Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.

basavarajnavalgund.github.io

tracking-with-Kalman-Filter

Object (e.g Pedestrian, biker, vehicles) tracking by Kalman Filter (KF), with fused data from both lidar and radar sensors.

tracking-with-Unscented-Kalman-Filter

Object (e.g Pedestrian, biker, vehicles) tracking by Unscented Kalman Filter (UKF), with fused data from both lidar and radar sensors.

Jupyter Notebook

udacity-cpp

Home-Service-Robot

Udacity Robotics Home Service Robot Project

PID-Control

Model-Predictive-Control

This project is to use Model Predictive Control (MPC) to drive a car in a game simulator. The server provides reference waypoints (yellow line in the demo video) via websocket, and we use MPC to compute steering and throttle commands to drive the car. The solution must be robust to 100ms latency, since it might encounter in real-world application.