We are developing level-5 autonomous driving technology. Our immediate next goal is to perform 100 KM/H autonomous driving demo on Indian roads, showcasing the capabilities of our technology.
Decision making and motion planning accounts for 70% of our R&D, where our research primarily focuses on reinforcement learning, and various areas of theoretical computer science and applied mathematics.
Earlier, we have been proving our technology: (i) in traffic scenarios with stochastic, complex, and often adversarial dynamics; and (ii) in unstructured environmental conditions in India. Furthermore, our R&D also focuses on enabling autonomous driving without the requirement of high-definition or high-fidelity maps.
Since 2016 we have been perform both the algorithmic as well as full autonomous driving demo, using our autonomous Mahindra Bolero vehicle (2016-2021). We have performed autonomous driving demo in 2017 and 2018 in extremely challenging tight traffic conditions on Indian roads.
Sanjeev initiated his research in autonomous navigation in unknown environments in January 2009, when he was an undergrad student at IIT Roorkee.
Since 2014, his research has spanned across several areas theoretical computer science and applied mathematics, focusing on applications in autonomous driving, including deep learning, computer vision, SLAM and visual odometry.
His research at Swaayatt Robots, to enable autonomous driving in environments as difficult as in India, has been covered by both the national and international media, on several occasions.