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A Reinforcement Learning based Path Planning Approach in 3D Environment
[article]
2022
arXiv
pre-print
Optimal motion planning involves obstacles avoidance where path planning is the key to success in optimal motion planning. Due to the computational demands, most of the path planning algorithms can not be employed for real-time based applications. Model-based reinforcement learning approaches for path planning have received certain success in the recent past. Yet, most of such approaches do not have deterministic output due to the randomness. We analyzed several types of reinforcement
arXiv:2105.10342v2
fatcat:ddnjtt2unveibd7ne5aju6rbra