Swaayatt (स्वायत्त) is a Sanskrit word, which means "autonomous". Swaayatt Robots is building self-driving vehicle technology that will be able to handle very complex traffic scenarios, such as the Indian traffic. Also, this technology is being developed taking the Indian road conditions into account.
Swaayatt has been bootstrapped for 2.5 years now, and currently located in Bhopal.
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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