Learning based multi-obstacle avoidance of unmanned aerial vehicles with a novel reward
Haochen Gao , Bin Kong , Miao Yu , Jinna Li
Complex Engineering Systems ›› 2023, Vol. 3 ›› Issue (4) : 21
Learning based multi-obstacle avoidance of unmanned aerial vehicles with a novel reward
In this paper, a novel reward-based learning method is proposed for unmanned aerial vehicles to achieve multi-obstacle avoidance. The Markov jump model was first formulated for the unmanned aerial vehicle obstacle avoidance problem. A distinctive reward shaping function is proposed to adaptively avoid obstacles and finally reach the target position via an optimal approach such that an adaptive Q-learning algorithm called the improved prioritized experience replay is developed. Simulation results show that the proposed algorithm can achieve autonomous obstacle avoidance in complex environments with improved performance.
UAVs / multi-obstacle avoidance / adaptive Q-learning
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Schaul T, Quan J, Antonoglou I, Silver D. Prioritized experience replay. arXiv 2016. Available from: https://arxiv.org/abs/1511.05952[Last accessed on 16 Aug 2023] |
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