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Development of a Robotic Arm-Gantry Simulator with Probabilistic Inference Based Control.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Development of a Robotic Arm-Gantry Simulator with Probabilistic Inference Based Control./
Author:	Syed, Shahbaz Peeran Qadri.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
Description:	88 p.
Notes:	Source: Masters Abstracts International, Volume: 84-06.
Contained By:	Masters Abstracts International84-06.
Subject:	Robotics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29164026
ISBN:	9798363505812

Development of a Robotic Arm-Gantry Simulator with Probabilistic Inference Based Control.
Syed, Shahbaz Peeran Qadri.

Development of a Robotic Arm-Gantry Simulator with Probabilistic Inference Based Control. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 88 p.

Source: Masters Abstracts International, Volume: 84-06.

Thesis (M.S.)--Oklahoma State University, 2022.

This item must not be sold to any third party vendors.

Robotic arms can perform repetitive tasks with high speed, accuracy, and precision, making them highly suitable for applications that are monotonous or require a high degree of precision. Such applications include industrial applications, human-robot collaboration applications, and experimental setups for model testing. A robust simulation as prototype testing is typically required to identify potential risks of catastrophic damage to the model or the experimental setup. Robot Operating System (ROS) is a widely-used framework for creating robotic applications both in research and in industry due to its easy hardware abstraction, code re-usability, and compatibility with popular open-source libraries. This thesis is focused on a robotic system consisting of a 7-DOF robotic arm ceiling mounted on a two-axis gantry. A simulator is developed for the 9-DOF robotic system in the ROS-Gazebo framework that interfaces with Moveit API for motion planning. A well-known Approximate Inference Control (AICO) algorithm is added to the simulator to extend its functionality to perform optimal trajectory planning. This work also extends the study of the AICO algorithm to non-holonomic mobile robots. Simulation experiments are conducted on both systems to study the behavior, performance, and limitations of AICO.

ISBN: 9798363505812Subjects--Topical Terms:

561941
Robotics.
Subjects--Index Terms:

Approximate inference

Development of a Robotic Arm-Gantry Simulator with Probabilistic Inference Based Control.
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520 $a Robotic arms can perform repetitive tasks with high speed, accuracy, and precision, making them highly suitable for applications that are monotonous or require a high degree of precision. Such applications include industrial applications, human-robot collaboration applications, and experimental setups for model testing. A robust simulation as prototype testing is typically required to identify potential risks of catastrophic damage to the model or the experimental setup. Robot Operating System (ROS) is a widely-used framework for creating robotic applications both in research and in industry due to its easy hardware abstraction, code re-usability, and compatibility with popular open-source libraries. This thesis is focused on a robotic system consisting of a 7-DOF robotic arm ceiling mounted on a two-axis gantry. A simulator is developed for the 9-DOF robotic system in the ROS-Gazebo framework that interfaces with Moveit API for motion planning. A well-known Approximate Inference Control (AICO) algorithm is added to the simulator to extend its functionality to perform optimal trajectory planning. This work also extends the study of the AICO algorithm to non-holonomic mobile robots. Simulation experiments are conducted on both systems to study the behavior, performance, and limitations of AICO.
590 $a School code: 0664.
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650 4 $a Mechanical engineering. $3 557493
653 $a Approximate inference
653 $a Planning
653 $a Robot operating system
653 $a Robotics
653 $a Simulation
653 $a Stochastic optimal control
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710 2 $a Oklahoma State University. $b Mechanical & Aerospace Engineering. $3 1413491
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