Updated: Jun 22
MIT researchers developed a system to be compatible with driver-less car; which has Human like reasoning to Autonomous vehicle Navigation.
To have human like Reasoning to autonomous vehicle navigation, MIT researchers have developed a system that enables a driver-less car to check simple map and use visual data to follow routes in a complex environment. Human drivers are exceptionally good at navigating roads they haven’t driven on before, using observation and simple tools. We simply match what we see around us to what we see on our GPS devices to determine where we are and where we need to go. Driverless cars, struggle with this basic reasoning. In every new area, the cars must first map and analyze all the new roads, which is very time consuming. The systems also rely on complex maps generated by 3-D scans which are computationally intensive to generate. In a paper presented at this week’s International Conference on Robotics and Automation, MIT researchers described an autonomous control system that learns the steering patterns of human drivers as they navigate through roads in a small area, using only data from video camera feeds and a simple GPS-like map. Then, the trained system can control a driver-less car along a planned route in a brand-new area, by imitating the human driver.
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