Please contact Dr. Works (keworks@fsu.eu) for additional help: Submission navigation links for Research Symposium Program Portal WF ‹ Previous submission Next submission › Submission information Submission Number: 133 Submission ID: 8416 Submission UUID: ebb69ecf-e385-45d8-860d-15aa1415a2a4 Submission URI: /student-research/symposium/research-symposium-program-portal Submission Update: /student-research/symposium/research-symposium-program-portal?token=6fNywzpQji9HIDbaN3FAgtImrrxeP76VIlij2lO1yvM Created: Wed, 03/05/2025 - 10:28 AM Completed: Wed, 03/05/2025 - 10:31 AM Changed: Mon, 04/14/2025 - 12:42 PM Remote IP address: 146.201.10.11 Submitted by: Anonymous Language: English Is draft: No Webform: Research Symposium Program Portal WF Submitted to: Student Research Symposium Program Portal Primary Student Contact First Name Primary Student Contact Last Name Pronouns Primary Student Contact FSU Student Email Photo of all individuals presenting this work PFP-Color.png12.17 MB Remove Upload requirementsOne file only.2 MB limit. Major(s) of all individuals presenting this work Bio of all individuals presenting this work Liliana Carlson is a senior in High School at Ohana Institute from Santa Rosa Beach, FL, with a passion for robotics, engineering, and physics. She has extensive experience in competitive robotics, serving as a FIRST Robotics Competition (FRC) team captain and mentor and leading FTC (FIRST Tech Challenge) projects focused on autonomous programming and drivetrain optimization. Liliana’s expertise includes probabilistic decision-making models, odometry tuning, and swerve drive calibration. In recognition of her leadership, technical skills, and dedication to STEM, she was named a 2024 FRC Dean’s List Finalist. Beyond robotics, Liliana has a strong academic foundation in physics and mathematics, pursuing advanced coursework in calculus and engineering. She is passionate about pushing the boundaries of automation and robotics and applying innovative problem-solving approaches to real-world challenges. Poster Title Abstract This paper explores the application of probabilistic decision-making models to enhance the efficiency and reliability of autonomous operation in FIRST Robotics Competition (FRC) robots. Traditional deterministic autonomous programs often struggle with variability in sensor data, drivetrain inconsistencies, and unforeseen obstacles, leading to suboptimal performance. Robots can dynamically adjust their actions based on real-time conditions by integrating probabilistic models, optimizing movement strategies, and increasing scoring efficiency. Drawing from research in autonomous vehicles and Bayesian networks, this study examines how probabilistic frameworks improve adaptability and decision-making in uncertain environments. Key findings demonstrate that probabilistic approaches enhance FRC autonomous strategies by enabling real-time adjustments, reducing error rates, and maximizing competitive performance. The results suggest that future FRC teams can benefit from incorporating probabilistic modeling techniques to develop more robust and flexible autonomous routines. Research Mentor Name Research Mentor's College (or High School) Research Mentor's Department (or Subject) Research Mentor's Email Additional Research Mentor(s) Co-presenter(s) Keywords Poster Session/Number Work Complete Exploratory (the research question has been identified and design of approach is outlined) Presentation Modality Face to Face Poster session Synchronous Online Presentation Asynchronous Online Presentation Poster PDF 2025 Student Research Symposium.pdf2.38 MB Remove Upload requirementsOne file only.100 MB limit. Poster Thumbnail Screenshot 2025-03-24 at 5.24.30 PM.png759.22 KB Remove Upload requirementsOne file only.2 MB limit. I will be printing my poster CAPTCHA What code is in the image? Enter the characters shown in the image. This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Save Leave this field blank
