#autonomousdriving

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Presenting autonomous driving in complex, stochastic and adversarial traffic-dynamics, on the roads in #India. Over the course of last year, we enabled #autonomousdriving in conditions and in situations no one in the autonomous driving industry considered was possible, and in a country like India, where the contemporary belief was that #autonomousvehicles are an impossibility. With the closure of 2023, we present autonomous driving at a very large scale, in the city of Bhopal in India. In this demo our autonomous vehicle at Swaayatt Robots can be seen negotiating the surrounding traffic with ease, where it had to deal with their stochastic and adversarial driving patterns, like suddenly switching lanes and appearing all of a sudden in our vehicle's current driving lane, without adherence to the traffic rules. This demo was a culmination of the cutting-edge research we have been doing, and the technologies we have been developing, over the years, which we showcased throughout in our demos in 2023 -- campus autonomous driving (February), off-roads autonomous driving (April and September), tight-stochastic traffic negotiation (August and September), bidirectional traffic negotiation on a single lane road (October), large-scale city level demo (November), and Toll-Plaza negotiation (December). In 2024, we will scale our technology commercially, and bring it to North America and Europe, to topple this trillion dollar industry, and will also scale our technology throughout India. Wishing everyone a very Happy New Year! #deeplearning #reinforcementlearning #MachineLearning Elon Musk PMO India Narendra Modi Nitin Gadkari DARPA DRDO

Sanjeev Sharma

95,416 Aufrufe • vor 2 Jahren

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Autonomous driving and obstacles avoidance at drift speeds, challenging the limits of what is possible! In this demo, our vehicle can be seen performing #autonomousdriving at very high speeds, causing it to both skid and drift at turns, while also avoiding obstacles. At such speeds, given the inherent dynamics of the vehicle platform used, it is very easy for the vehicle to topple. The #reinforcementlearning based motion planning and decision making framework that is being demoed here is tasked with ensuring obstacles avoidance without compromising on the speed, to an extent possible, and to drive the vehicle as fast as possible. This is evident towards the end of the video, where it can be seen that our vehicle avoided static obstacles while drifting.This demonstrates the level of sophistication and agility in our framework to ensure proper control of the #autonomousvehicles at high-speeds. The use cases are many; to begin with, our generic off-roads autonomous driving research focuses on enabling autonomous navigation in previously unknown and unseen environments, while ensuring mathematical completeness guarantees. Such agility can also help on-road autonomous vehicles to deal with unforeseeable corner cases or sudden appearance of obstacles in its tracks, at high-speeds. Our underlying research at Swaayatt Robots is still far from over, and over the next 3-4 months, we will be demonstrating abstract representation being learned by our multi-RL agents based framework (under progress) to ensure computation of the cost of the terrain without any labelled data, where multiple agents learn to control / regulate different aspects of autonomous navigation, to ensure safe and robust navigation, both on- and off-roads. All the people on the ground, who participated in the demo, were trained safety professionals. #deeplearning #MachineLearning #Robotics

Sanjeev Sharma

11,181 Aufrufe • vor 1 Jahr

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