Abstract

Achieving efficient and reliable performance with software frameworks is crucial for Autonomous Navigation with modern robotic systems. This research compares the Point Cloud Library (PCL) and the Robot Operating System (ROS) for autonomous navigation applications. The purpose of this research is to provide insights into comparative advantages and limitations of both frameworks, aiding researchers and developers with informed decision-making for their chosen autonomous systems.

A comprehensive evaluation will be conducted, encompassing various aspects such as sensor integration, perception algorithms, mapping, localization, and path planning. The evaluation will involve benchmarking experiments, where PCL and ROS are implemented and assessed in simulated and real-world autonomous navigation scenarios. Performance metrics, including processing time and accuracy , will be measured, documented and analyzed.

The results of this research will show the strengths and weaknesses of PCL and ROS, creating a comparative analysis of their features and limitations for autonomous navigation. The findings will highlight areas where each framework excels and where improvements are needed. Ultimately, this research plans to contribute insights to the field of autonomous navigation, to assist with the selection of suitable software frameworks and foster advancements in autonomous systems.

Roadmap

Week 2: Submit Written Abstract Week 3: Submit Research Proposal & Thank You Letters Week 4: Send Poster Final Draft to Mentors, Advisors. Practice 3 minute verbal thesis. Week 5: Poster Final Print. 3 Minute Verbal Thesis Preview. Week 5: Summer RAPS event. Present poster and 3 minute thesis. Week 5: focus group, debrief, summer post-experience reflection. Week 5: Done - take a mini vacation before Fall 2023 School Semester Starts.

Resources

Augmented Reality View: 3D Agile X Scout Mini Robot 3D Model by Yuan Shenghai Autonomous Navigation using LiDAR and Agile X Robotics rneddojr Blender Autonomous Navigation Comparative Analysis of ROS, PCL and Alternatives WIP Mathworks Autonomous Navigation Maya Autonomous Navigation MohawkLanguage.ca NVIDIA Isaac Sim NVIDIA Isaac Sim Tutorials NVIDIA Omniverse PointClouds.org RAPS 2023 Ros.org Synthetic Data Generation Unity Autonomous Navigation Unity Autonomous Navigation Robotics Kit Tutorial UnReal Engine Autonomous Navigation

Kanienkeha

Kanien’kéha English -- note pronunciations are not verified yet

kí:ken it's thí:ken it's Ioronhió:ron it's cloudy

ROBOT DESCRIPTIONS:

kahnh�htshera a servant konw�hnha's they employ it konwa'nikonhr�ta'as they give it sense karistot�ties metal that walks around orok�:ta orok�tshera Okwe teskaierontare kaia'ton:niserothatses needs more verification. possibly West Dialect)

Contact

MoniGarr - monigarr@MoniGarr.com

Github.com/monigarr/RAPS23_MoniGarr

Acknowledgements

MoniGarr acknowledges the following for supporting their summer research project:

Corning Inc. Clarkson University Honors Summer Research Program Advisors: Dr. Kate Krueger & Dr. Chen Liu Mentors: Irwing Vielma & Hovan Liu Computer Architecture and Microprocessor Engineering Lab (CAMEL) camel.clarkson.edu

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