dc.contributor.advisor | Ufodike, Chukwuzubelu | |
dc.creator | Ewelike, Chukwubuikem | |
dc.date.accessioned | 2023-10-12T13:44:11Z | |
dc.date.available | 2023-10-12T13:44:11Z | |
dc.date.created | 2023-08 | |
dc.date.issued | 2023-06-02 | |
dc.date.submitted | August 2023 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/199691 | |
dc.description.abstract | This thesis discusses complete coverage path planning (CPP) algorithms used for robotic systems in dynamic and changing environments. The focus is on the Neural Network algorithm [9] and its adaptation for practical use on an industrial-ready robotic platform. Various approaches to CPP are described, including offline and online algorithms, and a structured approach using grid mapping-based methods. The thesis also mentions the physical implementation of the algorithm on a multi-robotic system and discusses the limitations of current methods for industrial applications. The objective of the research is to develop a system for complete coverage path planning with higher coverage completeness, lower path repetition rate, and less path execution time. The research is limited to real-world simulations using Gazebo World and Robot Operating System (ROS). | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.subject | Path Planning | |
dc.subject | Complete Coverage Navigation | |
dc.subject | ROS | |
dc.subject | Neural Network | |
dc.subject | Robot Navigation | |
dc.title | Neural Network Algorithm for Complete Coverage Path Planning in Industrial Robotic Platforms: A Simulation-Based Study | |
dc.type | Thesis | |
thesis.degree.department | Engineering Technology and Industrial Distribution | |
thesis.degree.discipline | Engineering Technology | |
thesis.degree.grantor | Texas A&M University | |
thesis.degree.name | Master of Science | |
thesis.degree.level | Masters | |
dc.contributor.committeeMember | Darbha, Swaroop | |
dc.contributor.committeeMember | Nie, Xiaofeng | |
dc.type.material | text | |
dc.date.updated | 2023-10-12T13:44:12Z | |
local.etdauthor.orcid | 0009-0001-3905-5047 | |