Autonomous Trajectory Tracking and Obstacle Avoidance

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Autonomous Trajectory Tracking and Obstacle Avoidance

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Bereza-Jarocinski, Robert / Persson, Therese

Autonomous ground vehicles (AGVs), such as selfdrivingcars, are expected to become a central part of infrastructurein future smart cities. There are many technicalchallenges with making vehicles autonomous. They have to beable to find their way in both free environments as well asin environments with obstacles and other vehicles. To achievethis, they require many sensors to analyze their surroundings.The aim with this paper is to investigate the sensor typesnormally used in AGVs, describe their functionality and alsoprovide a model of how an autonomous vehicle can navigate indifferent environments, and verify this model through simulation.Lidar, Radar, accelerometers, gyroscopes, positioning systems andcameras are the sensors that are listed. It is described whatthey measure and what this data can be used for. To model theautonomous vehicle, a car-like vehicle model is used. A trajectorytracking controller is proposed, together with a proof of itsstability using Lyapunov functions. A way to avoid stationaryobstacles using potential fields is also described. Both the trackingcontroller and the obstacle avoidance controller are shown towork as expected through simulation. The used model only allowsfor the vehicle to travel in directions within a span of ±45 of itsforward direction. Lastly, a new application for AGVs in smartcities is also proposed.