A Computational Framework for Automatic Online Path Generation of Robotic Inspection Tasks via Coverage Planning and Reinforcement Learning
Surface/shape inspection is a common and highly repetitive task in the factory production line. Using robots to automate the inspection process could help to reduce the costs and improve the productivities. In robotized surface/shape inspection application, the planning problem is to find a near-opt...
Main Authors: | Wei Jing, Chun Fan Goh, Mabaran Rajaraman, Fei Gao, Sooho Park, Yong Liu, Kenji Shimada |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8476296/ |
Similar Items
-
Reinforcement Learning-Based Complete Area Coverage Path Planning for a Modified hTrihex Robot
by: Koppaka Ganesh Sai Apuroop, et al.
Published: (2021-02-01) -
A Reinforcement Learning Approach to View Planning for Automated Inspection Tasks
by: Christian Landgraf, et al.
Published: (2021-03-01) -
Deep Reinforcement Learning for Path Planning by Cooperative Robots: Existing Approaches and Challenges
by: Walaa Othman, et al.
Published: (2021-01-01) -
Reinforcement Learning-Based Energy-Aware Area Coverage for Reconfigurable hRombo Tiling Robot
by: Anh Vu Le, et al.
Published: (2020-01-01) -
On the Impact of Gravity Compensation on Reinforcement Learning in Goal-Reaching Tasks For Robotic Manipulators
by: Jonathan Fugal, et al.
Published: (2021-03-01)