Adversarial and Unstructured Environments via Reinforcement Learning

Motion Planning & Decision Making | Perception | Localization | Controls

More About


Make connected autonomous driving technology accessible, affordable and available to everyone! Significantly reduced Annotated data, Safe & Robust, Cost-Effective, and Mapless!

Autonomous Driving

AI Software Platforms and Solutions

Industrial and Warehouse Robotics

Research & Techstack

Our mission centers on the development of level-5 autonomous driving technology, striving for a future where vehicles can operate entirely independently. In line with this goal, our imminent objective is to conduct a compelling 100 KM/H autonomous driving demonstration on Indian roads. This demonstration will serve as a tangible showcase of our technology's remarkable capabilities, illustrating how our autonomous systems can navigate real-world environments at high speeds. By achieving this milestone, we're not only advancing the frontiers of self-driving technology but also bringing a clearer vision of the potential future of transportation to reality.

Our technology has undergone rigorous testing and validation across diverse scenarios to ensure its robustness and effectiveness. Specifically, we have conducted comprehensive trials in challenging areas

Traffic Scenarios with Stochastic, Complex, and Adversarial Dynamics- In this phase of testing, we immersed our technology in intricate traffic scenarios characterized by a multitude of variables and unpredictable behaviors. The dynamics of traffic are inherently stochastic

A significant portion of our research and development efforts, totaling 70%, is dedicated to decision making and motion planning. Within this realm, our focus lies on honing the intricacies of reinforcement learning, delving into diverse facets of theoretical computer science, and applying advanced mathematical principles. This concentrated effort allows us to cultivate a profound understanding of the mechanisms behind autonomous decision making and motion planning, positioning us at the forefront of crafting innovative solutions for the future of transportation.

Our advanced perception and behavior planning algorithms have reached a point where the necessity for high-definition 3D mapping of environments is greatly reduced. In the context of autonomous driving, dense maps no longer remain an indispensable component. Instead, we have demonstrated the capability to rely on GPS maps for seamless end-to-end navigation.

Prior Funding and Ecosystem Support