Projects

  • Description: This project involves the development of a multi-agent reinforcement learning (MARL) algorithm for swarm robotics, enabling multiple robots to work together to achieve a common goal in the context of autonomous navigation with obstacle avoidance.
  • Technologies Used: ROS2, PyTorch, Gazebo, Zenoh, Stable Baselines3
  • GitHub: View on GitHub

Coffee Robot: Personalize robot to deliver the coffee

  • Description: This project involves the development of a personal robot like turtlebot3 which is integrated with various sensors like LiDAR, IMU, camera, and wheel encoders for localization, mapping, navigation with path planning, and obstacle avoidance.
  • Technologies Used: ROS2, Nav2, LiDAR, IMU, MicroROS, Edge
  • GitHub: View on GitHub

Coffee Robot

  • Description: This project combines the power of LLM with Nav2 API to control the robot by just talking to the robot, which is how we suppose to talk with the robots.
  • Technologies Used: Ollama, Llama3, ROS2, Nav2, Whisper
  • GitHub: View on GitHub

Multi-robot Visual SLAM & Navigation

  • Description: This project involves the development of a multi-robot visual SLAM and navigation system that enables multiple robots to work together to build a map of an unknown environment and navigate through it using VSLAM and avoid dynamic obstacle with Nav2 using NvBlox costmap layer.
  • Technologies Used: ROS2, CuVSLAM, NvBlox, Nav2, Isaac Sim, Docker, Zenoh

Robot Application Stack

  • Description: This project is a robotics application stack that allows robotics applications to be written once and run anywhere. It enables real-time feedback between virtual and physical workspaces, and ensures robots can seamlessly operate in dynamic environments.
  • Technologies Used: ROS2, Gazebo Sim, MoveIt, MQTT
  • GitHub View on GitHub

Robot Application Stack

Sensor fusion for autonomous vehicles

  • Description: This project involves the development of a sensor fusion algorithm that combines data from multiple sensors (LiDAR, cameras, and radar) to improve the accuracy and reliability of object detection and tracking in autonomous vehicles.
  • Technologies Used: Kalman Filter, Carla, ROS2
  • GitHub: View on GitHub

Result

IO Gripper Controller

  • Description: This project involves the development of a gripper controller which is based on IO that allows for precise control of a robotic gripper using ROS2 Control. The controller is designed to work with various types of grippers which can be configured using params yaml file and can be easily integrated into existing robotic systems.
  • Technologies Used: ROS2, ROS2 Controller, ROS2 Control
  • GitHub: View on GitHub