scholarly journals Dynamic Planning Method Based on Time Delayed Q-Learning

2017 ◽  
Vol 07 (07) ◽  
pp. 671-677
Author(s):  
夏 庄
Keyword(s):  
Planning Method ◽  
Dynamic Planning ◽  
Q Learning

Research on Dynamic Planning Method of Collision Avoidance Route Based on Ship Kinematics

2021 ◽  
Author(s):  
Lipeng Wang ◽  
Chenkun Zhou ◽  
Zhi Zhang ◽  
Shan Ma ◽  
Wenlong Ma
Keyword(s):  
Collision Avoidance ◽  
Planning Method ◽  
Dynamic Planning

scholarly journals A Novel Hybrid Path Planning Method Based on Q-Learning and Neural Network for Robot Arm

2021 ◽  
Vol 11 (15) ◽  
pp. 6770
Author(s):  
Ali Abdi ◽  
Dibash Adhikari ◽  
Ju Hong Park
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Learning Algorithm ◽  
Hybrid Approach ◽  
Active Phase ◽  
Planning Method ◽  
Environment Interaction ◽  
Robot Arm ◽  
Q Learning ◽  
Passive Phase

Path planning for robot arms to reach a target and avoid obstacles has had a crucial role in manufacturing automation. Although many path planning algorithms, including RRT, APF, PRM, and RL-based, have been presented, they have many problems: a time-consuming process, high computational costs, slowness, non-optimal paths, irregular paths, failure to find a path, and complexity. Scholars have tried to address some of these issues. However, those methods still suffer from slowness and complexity. In order to address these two limitations, this paper presents a new hybrid path planning method that contains two separate parts: action-finding (active approach) and angle-finding (passive approach). In the active phase, the Q-learning algorithm is used to find a sequence of simple actions, including up, down, left, and right, to reach the target cell in a gridded workspace. In the passive phase, the joints angles of the robot arm, with respect to the found actions, are obtained by the trained neural network. The simulation and test results show that this hybrid approach significantly improves the slowness and complexity due to using the simplified agent-environment interaction in the active phase and simple computing the joints angles in the passive phase.

A Path Planning Method for Multi-robot Formation Based on Improved Q-Learning

2021 ◽  
pp. 842-849
Author(s):  
Zhilin Fan ◽  
Hongyong Yang ◽  
Yilin Han ◽  
Xinshun Ning
Keyword(s):  
Path Planning ◽  
Planning Method ◽  
Q Learning ◽  
Multi Robot

scholarly journals Dynamic Planning Method for Drug Distribution in Earthquake Response Based on Sliding Time Window Series

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 160697-160710
Author(s):  
Jiaqi Fang ◽  
Hanping Hou ◽  
Lingle Pan ◽  
Qingshan Deng ◽  
Haiyun Pang ◽  
...  
Keyword(s):  
Time Window ◽  
Drug Distribution ◽  
Planning Method ◽  
Earthquake Response ◽  
Dynamic Planning
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