An Improved HM-SAC-CA Algorithm for Mobile Robot Path Planning in Unknown Complex Environments

An Improved HM-SAC-CA Algorithm for Mobile Robot Path Planning in Unknown Complex Environments

Path planning and its optimization is a critical and difficult task for a mobile robot in a complex and unknown environment. To tackle this problem, we propose an improved SAC (HM-SAC-CA) algorithm for path planning in unknown complex environments. First, based on the SAC maximum entropy framework,...

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Bibliographic Details
Main Authors: Ting Jiao, Conglin Hu, Lingxin Kong, Xihao Zhao, Zhongbao Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Complex environment
deep reinforcement learning
mobile robot
path planning
Online Access:https://ieeexplore.ieee.org/document/10856113/
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https://ieeexplore.ieee.org/document/10856113/

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