Unique Applications

11:00 AM – BYU Mars Rover Telemetry in the 2025 University Rover Challenge
Nelson Durrant, Braden Meyers, Hannah Spigarelli, and Marc Killpack, Brigham Young University

As part of a senior-level capstone design course, our team designed, developed, and built a planetary rover for the University Rover Challenge (URC), capable of autonomous and manual remote operation. This paper presents and discusses the role of telemetry systems in facilitating communication between sensors onboard the rover and the base-station computer. The rover featured several critical subsystems, including a wirelessly-controlled differential drive system, localization, navigation, and perception solutions, a science module, and a 6-DOF robotic arm. These subsystems shared information with the base-station computer over a long-range antenna using ROS 1 and ROS 2. Overall, we focused on implementing robust and reliable communication approaches to ensure low-latency operation, given the URC’s long-range, bandwidth-limited connection requirements.

11:20 AM – Autonomous Control in Beetleweight Combat Robotics Using Computer Vision
Nikoli Cooper, Arlo Millis, and Dr. Michael Marcellin, University of Arizona

Beetleweight Combat Robotics is an event-driven sport consisting of two or more opposing, three pound robots in an enclosed arena, traditionally remotely controlled by a pilot. A novel alternative to the standard human pilot is an autonomous control algorithm using computer vision via a top-down orthographic camera. A closed-loop control algorithm is implemented, in which robots in an arena are detected and subsequent motion correction is calculated and relayed to the autonomous robot. Autonomous control carries the benefit of removing human reaction time while increasing command frequency, which improves the resolution of control over a standard human pilot. A Combat Robotics arena provides a consistent testing ground for autonomous control where complex object interaction is analyzed with computer vision. Consequently, this experience enables motivated engineers in the Wildcat Robotics Club at the University of Arizona to gain experience with computer vision and develop the skills required to advance the state of self driving technology in motorized vehicles.

11:40 AM – Hardware-Software Co-Design of Integrative Telemetry System for Off-Road Racing Vehicle
Dylan Correa, Matthew Larson, Julian Pimienta Rendon, Karsten Yin, Jack Tanner, Connor Larson, Finn Geber, Benedict Colombi, Lily Hall, and Dr. Michael Marcellin, University of Arizona

The University of Arizona Baja Wildcat Racing Team’s integrative off road telemetry system merges custom circuit boards and a C#-based, GPU-accelerated GUI. Utilizing CAN-bus, I2C, and SPI protocols alongside NRF24L01 devices for wireless communication, it collected data via IMUs, temperature sensing devices, three speed sensors, an induction-based tachometer using spark plug driven input, and pressure transducers. The system monitored RPMs, positional data, and brake actuation, enhancing real-time data visualization through an improved dashboard interface. Hardware and software advancements significantly refined telemetry accuracy and driving insights, optimizing vehicle performance. This innovation demonstrates a leap forward in the university’s off-road racing telemetry.

12:00 PM– Telemetry-Driven Electrical System to Optimize Engine Performance
Aidan Brown, Bea Goco, Joseph Mclaughlin, and Dr. Michael Marcellin, University of Arizona

The Wildcat Formula Racing (WFR) team of the University of Arizona designed and built an electrical system for the team’s race car which requires a telemetry system to tune the engine. The electrical system was based upon previous designs and focused on accurately reading data from the various sensors to the ECU (Electronic Control Unit). Such sensors include the manifold absolute pressure sensor, throttle position sensor, air temperature sensor, etc. The ECU calculates the data into a readable graph which the team takes into account to optimize for peak performance. Through the integration of telemetry, the team is able to monitor the engine and ensure maximum efficiency.