taking one step at a time towards bringing autonomy to the real world

Welcome

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.

COMPUTER VISION

Traditional Computer Vision applications such as Structure from Motion (SfM), Stereo Rectification, Homography, etc.

MACHINE LEARNING

Machine Learning applications such as Object Detection, Depth Estimation, Meta Learning, etc.

DEEP REINFORCEMENT LEARNING

DRL examples in various environment setting, both single and multi-agent.

ROBOTICS

Autonomous Vehicle Software Stack and a Simple Autonomous Robot Navigation Implementation Example

Towards Autonomy Perception Library (TAPL)

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About Me

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