Micaela Mara Possetto
Experimental setup for collision avoidance algorithms for mobile robots.
Rel. Stefano Mauro, Matteo Melchiorre. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022
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Abstract
Collision avoidance is a topic of utmost relevance in mobile robot navigation, where robots should be able to reach a goal and to avoid obstacles on their way autonomously, to operate consistently in a real-life environment. For this purpose, several algorithms have been developed over the last years. This work aims at providing a real-time collision-free path for mobile robots, implementing in real world a pre-existent collision avoidance algorithm, which has been tested so far in a simulation setting only. Specifically, the chosen technique improves the classical artificial potential fields by considering local attractors in addition to repulsors, in order to drive the robot towards a goal, while avoiding obstacles along preferred directions.
The first phase consisted in reproducing the conditions of the simulated environment in a laboratory setup made of a single obstacle and a mobile robot controlled by the algorithm, that has been implemented in ROS (Robot Operating System)
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