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    MQTPP – Towards Multiple Q-Table based Path Planning in UAV Environments

    Jones, Michael Richard, Djahel, Soufiene ORCID logoORCID: https://orcid.org/0000-0002-1286-7037 and Welsh, Kristopher (2022) MQTPP – Towards Multiple Q-Table based Path Planning in UAV Environments. In: 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 08 January 2022 - 11 January 2022, Las Vegas, NV, USA.

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    Abstract

    This paper introduces an original multi destination path planning approach for Unmanned Aerial Vehicles (UAVs) named MQTPP (Multi Q-Table Path Planning). MQTPP aims to reduce the computational burden of cyclical/continuous path planning through a Q-learning planning process whilst overcoming the fixed path origin problem. The preliminary performance evaluation results indicate that MQTPP performs well for longer paths, and allows for more efficient re-planning should mission objectives or environmental topography change.

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