IIIT Hyderabad fuses AI and Robotics for intelligent self-driving systems

IIIT Hyderabad has developed an electric self-driving car designed to autonomously navigate point-to-point routes with advanced collision avoidance mechanisms. While these maps are metrically less accurate, IIITH enhances their usability by integrating them with contextual language landmarks, such as “under the bridge” or “near the playground.” This technique enables the car to navigate dynamically to new locations without explicit prior training, offering remarkable zero-shot generalisation capabilities. BRIDGING CLASSICAL ROBOTICS AND MODERN AI IIIT Hyderabad’s autonomous driving team leverages foundational AI models with robust semantic understanding achieving precise localisation and navigation. Traditionally, navigation pipelines separated these tasks, but IIITH’s car adopts a vision-language integration approach, which enhances its ability to process natural language commands like “take a left near the food stall.” To address the inherent challenges in perception-based navigation, the system employs a differentiable planning module within its neural network framework. By integrating AI-driven vision-language models with robust planning frameworks, IIIT Hyderabad’s autonomous driving system represents a transformative leap in robotics research.