Date of Award

12-2023

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical and Civil Engineering

First Advisor

Seong Hyeon Hong, Ph.D.

Second Advisor

Madhur Tiwari, Ph.D.

Third Advisor

Kim-Doang Nguyen, Ph.D.

Fourth Advisor

Ashok Pandit, Ph.D. P.E.

Abstract

Planetary exploration relies on methods of path planning to achieve autonomous navigation in hazardous environments. Simulating harsh terrain, real-time varying physics, and robotics applications is vital for testing control algorithms here on Earth. Robotics Operating System (ROS) is a set of software libraries and tools that allow you to build and simulate robotic applications. Utilizing ROS, Gazebo, and Blender, a rough terrain simulation framework is created to explore and compare path planning algorithms using various desired robots and maps. ROS supports multiple path planning algorithms given its open-source abilities. This research focuses on path planning implementation of Proportional-Integral-Derivative (PID) control and the Model Predictive Control (MPC) as they navigate the Husky model robot to multiple waypoints in a developed framework. The path planning framework successfully integrated both controllers enabling the robot to follow desired paths. To execute PID, the algorithm is approximated as two separate subsystems: rotational and translational. The subsystems are designed to control the position and orientation of the robot. Conversely, MPC controls the entire system utilizing the coupled equations of motion. The ROS path planning framework developed will support future scientific research and provide a basis for testing path planning algorithms.

Comments

Copyright is held by author.

Download

Share

COinS