A Deep Reinforcement Learning Method for Mobile Robot Collision Avoidance based on Double DQN

2019 ◽  
Author(s):  
Xidi Xue ◽  
Zhan Li ◽  
Dongsheng Zhang ◽  
Yingxin Yan
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Collision Avoidance ◽  
Learning Method

scholarly journals Autonomous Navigation Using Deep Reinforcement Learning in ROS

2021 ◽  
Vol 11 (2) ◽  
pp. 63-70
Author(s):  
Ganesh Khekare ◽  
Shahrukh Sheikh
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Social Norms ◽  
Collision Avoidance ◽  
Human Behavior ◽  
Autonomous Navigation ◽  
Autonomous Robot ◽  
Stochastic Behavior ◽  
Human Behaviors ◽  
Navigation Scheme

For an autonomous robot to move safely in an environment where people are around and moving dynamically without knowing their goal position, it is required to set navigation rules and human behaviors. This problem is challenging with the highly stochastic behavior of people. Previous methods believe to provide features of human behavior, but these features vary from person to person. The method focuses on setting social norms that are telling the robot what not to do. With deep reinforcement learning, it has become possible to set a time-efficient navigation scheme that regulates social norms. The solution enables mobile robot full autonomy along with collision avoidance in people rich environment.

scholarly journals 2A1-E17 Two-dimensional Motion Acquisition of a Mobile Robot by Reinforcement Learning Method

2006 ◽  
Vol 2006 (0) ◽  
pp. _2A1-E17_1-_2A1-E17_4
Author(s):  
Masashi INOUE ◽  
Masataka SAO ◽  
Masayuki HARA ◽  
Jian HUANG ◽  
Tetsuro YABUTA
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Learning Method ◽  
Two Dimensional
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