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Reactive Vision-Based Navigation Controller for Autonomous Mobile Agents

  • Initial results of an ongoing research in the field of reactive mobile autonomy are presented. The aim is to create a reactive obstacle avoidance method for mobile agent operating in dynamic, unstructured, and unpredictable environment. The method is inspired by the stimulus-response behavior of simple animals. An obstacle avoidance controller is developed that uses raw visual information of the environment. It employs reinforcement learning and is therefore capable of self-developing. This should result with obstacle avoidance behavior that is adaptable and therefore generalizes on various operational modalities. The general assumptions of the agent capabilities, the features of the environment as well as the initial result of the simulation are presented. The plans for improvement and suitable performance evaluation are suggested.

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Author:Ruben Nuredini
Document Type:Preprint
Year of Completion:2014
Release Date:2017/03/13
Tag:intelligent mobile agent; reactive obstacle avoidance; reinforcement learning
Pagenumber:6 Seiten
Preprint; bei Journal of computers, ISSN 1796-203X zur Veröffentlichung im Sommer 2017 angenommen
Access Right:Frei zugänglich
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung