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