Exploration of Unknown Environments Using Deep Reinforcement Learning

Authors

  • Joseph McCalmon Wake Forest University

Keywords:

Autonomous Exploration, Reinforcement Learning, LSTM, Deep Learning

Abstract

My research presents a method for efficient exploration of an outdoor, unknown area, which aims to achieve precise coverage of regions of interest within that area. While this method for autonomous exploration was designed for autonomous controllers in unmanned aerial vehicles (UAVs), the concepts apply to any vehicle which uses autonomous navigation. We consider an environment with areas of interest of various sizes littered throughout, and a reinforcement learning agent which is tasked with discovering and mapping these areas in an efficient manner.

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Published

2021-05-18

How to Cite

McCalmon, J. . (2021). Exploration of Unknown Environments Using Deep Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15970-15971. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17981

Issue

Section

AAAI Undergraduate Consortium