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This paper presents a method for observational learning in autonomous agents. A formalism based on deep learning implementations of variational methods and Bayesian filtering theory is presented. It is explained how the proposed method is capable of modeling the environment to mimic behaviors in an observed interaction by building internal representations and discovering temporal and causal relations...
Driverless vehicles have received a great deal of attention in the Intelligent Transportation Systems (ITS) research fields during the last decade. Moreover, with the release of several intelligent vehicles to the roads, the necessity of cooperation and coordination among the vehicles, infrastructure and road users is increasing. In order to implement these approaches, a proper communication architecture...
During the last decade, ground mobile robots that are able to drive autonomously in off-road environments have received a great deal of attention. Autonomous navigation in unstructured environments faces many new challenges compared to structured urban environments, these challenges increase the complexity of the localization, obstacle detection, path planning and navigation commands. Accordingly...
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