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Author ORCID Identifier

https://orcid.org/0000-0002-8650-5063

Date Available

5-10-2023

Year of Publication

2023

Document Type

Master's Thesis

Degree Name

Master of Science in Mechanical Engineering (MSME)

College

Engineering

Department/School/Program

Mechanical Engineering

Faculty

Dr. Hasan Poonawala

Faculty

Dr. Jonathan Wenk

Abstract

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network frequency requirements of the control signal for a real robotic system.

We develop and implement a parallelized version of RT-RRT*, dubbed Parallel RT-RRT* (PRT-RRT*), that can update motion plans in a dynamic environment while sending control signals at a high frequency. To achieve this, PRT-RRT* establishes a method of efficient communication between separate collision detection, path planning, and control nodes. We show that PRT-RRT* is capable of solving the dynamic path-planning problem on the 7D Franka Emika Panda robotic arm.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2023.194

Funding Information

This study was supported by the University of Kentucky Department of Mechanical Engineering

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