Towards Autonomous 1/8th Offroad RC Racing -- The TruggySense Educational Platform

TL;DR

The paper addresses the need for stability-focused ADAS in off-road RC racing by introducing a robust Data Acquisition System (DAQ) deployed on the Team Corally Kagama 1/8 vehicle to provide ground-truth data for education and ADAS development. It details a hardware architecture that integrates sensors (wheel encoders, BNO085 IMU, DS18B20 temperature sensors, GPS) with a Low-Level Controller and telemetry, paired with a 2.4 GHz wireless link for real-time monitoring. Through four controlled experiments on a challenging track, the DAQ demonstrates accuracy, repeatability, and resilience, including operation under crash conditions, while also highlighting current limitations such as missing per-motor current measurement and lack of redundancy. The work establishes a foundation for engineering education and ADAS algorithm validation in off-road RC contexts, with clear pathways toward a fully integrated, autonomous platform and future safety features.

Abstract

This paper presents a state-of-the-art Data Acquisition System designed for off-road conditions, deployed on a Team Corally Kagama 1/8 Remote Controlled Vehicle. The system is intended to support Advanced Driver Assistance Systems in an educational context by providing valuable, consistent, and representative data. Key measurement systems are discussed to enable insights into the Remote Controlled Vehicles stability during and after off-road races. Furthermore, four experiments where conducted to evaluate the Data Acquisition Systems accuracy, stability, and consistency in replicating real-world vehicle behavior. The proposed Data Acquisition System platform serves as a solid foundation for use in engineering education, enabling integration with various Advanced Driver Assistance Systems algorithms to enhance vehicle control and overall performance, offering a new dimension to off-road racing. Additionally, realtime telemetry enables verification and validation of Advanced Driver Assistance Systems algorithms based on the live operating state of the Radio Controlled Vehicle during races

Figures (8)

• Figure 1: (a) representing the abstract block diagram that covers the entire system of the framework. Here, the LLC is our DAQ which will capture various sensors such as the GPS, encoders for all wheels and motors, IMU, etc. Additionally, the LLC is responsible for actuating components such as the ESCs and the steering servo of the RCV, denoted as the RC-Controller block. Lastly the Real-time Communication module providing telemetry to the base station. (b) representing the hardware layout which is used on the Corally Kagama chassis where (b).a is the base plate used for mounting various modules, (b).b the LLC, (b).c the HLC, (b).d a 5.1 V 4 A DC-DC step-down converter, (b).e a 3.3 V 1 A DC-DC step-down converter, (b).f the GPS module, and (b).g X6B RF receiver (b).h NRF24 telemetry module. (c) depicts the chassis in its bare essence without the base plate mounted. (c).a the wheel encoders, (c).b the ESC to actuate the used brusheless motor, (c).c the brusheless motor, (c).d the steering servo, (c).e the IMU, and (c).f the temperature sensors.
• Figure 2: The used encoder ring structure where $X$ neodymium permanent magnets are utilized to determine the wheel speed. Here, six magnets are presented whereas in the used platform, 14 magnets are utilized.
• Figure 3: The Euler angles expressed as yaw $\alpha$, pitch $\beta$, and roll $\gamma$ on the Team Corally Truggy 1/8 RCV platform on the XYZ-axis of the RCV.
• Figure 4: The used test trajectory maintained by RC Racing Fun Bornem located at Bornem, Antwerp, Belgium. There are different terrain features embedded in the track such as hills, uneven terrain, a tunnel, sharp corners, and straight paths, making this track a challenge to drive. Therefore, this track is suited for the test environment as different elements can be tested such as traction on the road, suspension system, stability with respect to cornerings, etc. This track has a one way direction denoted by the arrow. This drive direction is always used in each race.
• Figure 5: Results of experiment 1: Slow driving over the track. Here, tree laps are driven. (a) representing the slow driven track GPS data path. One can see that the data acquired form the three laps do indeed have a correlation in terms of GPS position. Nevertheless, some small deviations are still visible due to the drivers chosen paths. (b) representing the pitch angle of three laps where similarities can be observed at the locations of bumps. Furthermore, a consistency of the sampled pitch data is present at similar bumps. Note that a positive pitch represents a downwards movement and a negative pitch, an upwards movement. (d) represent the difference between all wheels. It can be observed that in turnings, wheel speed differs due to the differentials in place. The used scale is normalized to give a clear difference.