Research Intern- Autonomous Perception & Navigation Systems

About the Role

We’re seeking a Research Intern passionate about applying AI and machine learning to autonomous UAV perception and navigation . You’ll explore and prototype learning-based algorithms that help drones see, localize, and move intelligently — even in dynamic or GPS-denied environments.

This internship provides hands-on exposure to simulation environments, sensor-fusion pipelines, and embedded AI systems.

Key Responsibilities :

Support research and prototyping of AI / ML algorithms for perception, tracking, localization and navigation.

Work on multi-sensor fusion combining visual, inertial, and positional data for improved environmental understanding.

Train and test computer vision or deep learning models for detection, motion estimation, and environmental understanding .

Use high-fidelity simulations with physics-based environments to generate datasets and test autonomy pipelines.

Assist in integrating perception and navigation modules into flight-control or hardware-in-the-loop setups.

Optimize real-time inference and video / data streaming pipelines for embedded AI systems.

Skills & Qualifications :

Strong foundation in deep learning, computer vision, and state estimation .

Understanding of object detection, tracking, SLAM, and sensor-fusion techniques .

Proficiency in Python and familiarity with PyTorch / TensorFlow and OpenCV .

Experience working on Linux environments and basic knowledge of C++ .

Familiarity with simulation tools (Gazebo, Webots, Isaac Sim) and autopilot frameworks (PX4, ArduPilot).

What you'll Gain :

End-to-end exposure to AI-driven autonomous navigation and perception systems .

Experience with simulation-driven development and testing of UAV autonomy algorithms.

Practical exposure to real-time AI model deployment on embedded hardware.

Opportunity to contribute to next-generation UAV guidance and autonomy research