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Hybrid of representation learning and reinforcement learning for dynamic and complex robotic motion planning
Reinforcement learning algorithms generate optimal or near-optimal time-sequential predictions.
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review
Fifth, we systematically present the hybridization of Bayesian inference and RL which is a promising direction to improve the convergence of RL for better motion planning.
An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios
Intelligent robots provide a new insight into efficiency improvement in industrial and service scenarios to replace human labor.
A review of motion planning algorithms for intelligent robotics
These include traditional planning algorithms, supervised learning, optimal value reinforcement learning, policy gradient reinforcement learning.
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