Overview
We are responsible for developing algorithms and systems that enable the autonomous vehicle to navigate, make decisions, and respond to the environment it encounters on the road.
Path Planning: These are algorithms for the best route considering road conditions, traffic signals, lanes, and obstacles.
Trajectory Following: This entails guiding the vehicle along a precise path, providing velocity and steering commands
Obstacle Avoidance & Decision Making: Autonomous vehicles need to make real-time decisions based on the information gathered from sensors and the surrounding environment. Leveraging data from cameras, LiDAR, and radar, the car determines its response to objects, pedestrians, and vehicles, ensuring safe navigation. The team creates algorithms that help the vehicle determine actions like lane changes, merging onto highways, overtaking vehicles, and handling complex traffic scenarios.
Team Lead: Keshav Bagri and Rahul Mathias
What will you learn?
In-depth understanding and implementation of control algorithms
Working knowledge on HIL/SIL testing
Advanced MATLAB/SIMULINK , dSPACE, Python, C++
Overall working knowledge of a self-driving car
Desired skills:
Dedicated students who have basic Programming skills
Basic proficiency in MATLAB/SIMULINK
Experience with ROS will be preferred
Internship or work experience in automotive/robotics field
Knowledge in Controls domain