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In this work, we present a software architecture to solve, at some level, the follow the leader problem. This problem consists of an autonomous vehicle trying to track and follow a leader vehicle. To track the leader position in consecutive camera images, we employed the Generic Object Tracking Using Regression Networks (GOTURN). GOTURN is a pre-trained Deep Neural Network capable of tracking generic...
We propose a Neural Based Model Predictive Control (N-MPC) approach to tackle delays in the steering plant of autonomous cars. We examined the N-MPC approach as an alternative for the implementation of the Intelligent and Autonomous Robotic Automobile (IARA) steering control subsystem. For that, we compared the standard solution, based on the Proportional Integral Derivative (PID) control approach,...
We present a simple yet effective obstacle avoider for the Intelligent and Autonomous Robotic Automobile (IARA). At each or several motion planning cycles, the IARA's obstacle avoider firstly receives as input an updated map of the environment around the car, the current car's state relative to the map, and a trajectory from the current car's state to the next goal state. Secondly, the obstacle avoider...
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