About Us


Swaayatt (स्वायत्त) is a Sanskrit word, which means "autonomous". Swaayatt Robots is primarily developing L4 and L5 self-driving technology, that works in extremely difficult traffic and (often-) unstructured environmental conditions like in India. The technology being developed is also generally applicable to mobile robots navigation, for both indoor (like in warehouses and industrial) and outdoor navigation (like agricultural domains / farms) tasks.

Swaayatt Robots is also developing “Swaayatt Driver Assistance System” (S-DAS). S-DAS can assist drivers in lane keeping even in the absence of explicit lane markers on the roads, as one of the software of S-DAS generates lane markers, where they ideally should have been, on the roads if they are not present or have faded away (often the case with Indian roads and highways).

Swaayatt has been bootstrapped for 2.5 years now, and currently located in Bhopal.


Sanjeev Sharma
Founder and Director

Sanjeev got his B. Tech in Electrical Engineering from IIT Roorkee in 2011 and attended University of Alberta for Masters in Computing Science (2012-2014). It was in January 2009 that he learned about the DARPA Grand and Urban Challenges, and this video by the Team MIT inspired his research in the field of artificial intelligence (AI) and autonomous navigation. In June 2009, he co-founded a webportal named "Searching-Eye" through which he started delivering his video lectures/tutorials in AI and optimization. During the Summer of 2010, he interned under Professor Sridhar Mahadevan, at the University of Massachusetts Amherst, in reinforcement learning. After graduating from IIT Roorkee, he self-initiated various research projects, creating motion planning algorithms with Indian enviroments in mind, which are now playing a key role in solving the self-driving problem at Swaayatt Robots. During September 2011 - April 2012 he interned under Professor Zvi Shiller, at Ariel University in Israel, where he developed a motion planner to help robots navigate in dense environments at high speeds. His Masters thesis adviser was Professor Richard S. Sutton, one of the pioneers of Reinforcement Learning. From August 2011 to September 2013 he also worked remotely under Professsor Matthew Taylor in reinforcement learning and motion planning.

In 2014, he returned to India, to finally convert his dream of building a self-driving vehicle, which he had since 2009, for India into a reality. At Swaayatt Robots, his primary research includes: (i) developing navigation and motion planning modules for solving the self-drving navigation problem in India; (ii) developing decision making frameworks for the self-driving vehicle; (iii) developing new deep learning frameworks to help the robots perceive their surroundings using the off-the-shelf cameras; (iv) developing intelligent control modules (such as the steering controller, and for various other controllers); and (v) developing a vision based vehicle localization framework to enable navigation in GPS-denied enviroments.


LinkedIn Profile; His old homepage (at searching-eye.com; maintained from 2010-2014): sanjeevs; Download: CV (Note: Last modified in December 2013; to be updated soon)
Research Areas: Machine Learning (including Reinforcement Learning and Deep Learning); Motion and Path Planning; Autonomous Navigation; Computer Vision (self-driving perception); Mathematical Optimization; and Multi-Agent Systems



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