taking one step at a time towards bringing autonomy to the real world
This website explores some major components needed to achieve complete autonomy in near future. It encompasses fields such as - Computer Vision, Machine Learning, Path Planning, Sensor Fusion, Robotics, and Controls. It also provides detailed insights on some of these components and provides a hands-on walkthrough. Towards Autonomy also provides access to a free open source perception library, TAPL, which is intended to help with easy implementation of perception tasks. Any contribution to this platform is welcome and appreciated.
Traditional Computer Vision applications such as Structure from Motion (SfM), Stereo Rectification, Homography, etc.
Machine Learning applications such as Object Detection, Depth Estimation, Meta Learning, Natural Language Processing etc.
DEEP REINFORCEMENT LEARNING
DRL examples in various environment setting, both single and multi-agent.
Autonomous Vehicle Software Stack and a Simple Autonomous Robot Navigation Implementation Example
An autonomous-driving and robotics technology enthusiast who envisions to invent technologies and bringing them to life, working towards making the autonomous car perceive the world like humans do.
Machine Learning and Computer Vision Research Scientist @ Ford Greenfield Labs
Graduate Student @ Stanford University