Research

My research focuses on developing intelligent autonomous robotic systems capable of operating safely and efficiently in complex real-world environments. I am particularly interested in perception-driven autonomy for resource-constrained robots, combining computer vision, deep reinforcement learning, and embedded AI.

My current research directions include:

• Vision-Based Autonomous Navigation using monocular cameras
• Tiny Drone Autonomy for indoor and GPS-denied environments
• Vision-Language-Action (VLA) Models for robotic navigation
• Deep Reinforcement Learning for obstacle avoidance and motion planning
• TinyML and Edge AI for battery-powered and batteryless devices
• Simulation-to-Real Transfer using ROS, Gazebo, Isaac Sim, and Webots

My long-term goal is to develop intelligent robotic systems that can perceive, reason, and navigate autonomously while operating under strict computational and energy constraints.