Data-Driven Motion Planning: A Survey on Deep Neural Networks, RL, and LLM Approaches
2025年1月1日·
·
0 min read
Takato Horii
Authors
Gabriel Peixoto De Carvalho, Tetsuya Sawanobori, Takato Horii
Abstract
A comprehensive survey of data-driven motion planning using deep neural networks, reinforcement learning, and large language models. We systematically organize state-of-the-art methods for robot motion planning and outline future research directions.
Type
Publication
IEEE Access, 13
Authors
Takato Horii
(he/him)
Associate Professor
Associate Professor at Graduate School of Engineering Science, Osaka University.
Research interests include cognitive developmental robotics, computational modeling
of emotional development, and human-robot interaction.