NXP AIM 2025 - Regional Finalist in AI Mobility Challenge

I recently took part in NXP AIM 2025 (Artificial Intelligence in Mobility) and managed to reach the regional finals. Though I didn't win, just getting selected from all the participants felt pretty amazing.

The regional finale took place at M.S. Ramaiah Institute of Technology, Bengaluru, which was an exciting experience competing alongside other talented teams from across the region.

AIM is basically a competition where engineering students get to work with AI and robotics for mobility applications. We had to build mobile robot prototypes using technologies like AI/ML, object recognition, sensors, computer vision, and obstacle avoidance.

The Challenge:

The main task was a robotic treasure hunt that tested both simulation and real-world robotics skills. Our robots had to navigate through complex environments, detect objects, avoid obstacles, and complete autonomous missions on their own.

What I worked with:

• ROS2 for the robot operating system and distributed robotics

• Gazebo for 3D robotics simulation

• Python for writing the main algorithms

• Foxglove for visualizing data and debugging

• Shell scripting for automation and system integration

• OpenCV for computer vision and image processing

• SLAM for simultaneous localization and mapping

• Nav2 for autonomous navigation

This experience really pushed my robotics and AI knowledge forward. Working with SLAM to map unknown environments and using Nav2 for autonomous navigation was tough but really rewarding. Getting to work with both simulation in Gazebo and real hardware gave me a much better understanding of how mobile robotics actually works.

Even though I didn't win the regional finals, I learned a ton about AI applications in mobility and it definitely strengthened my interest in robotics and autonomous systems.