# Advancing Road Infrastructure Safety with the Remotely Piloted Safety Cone
## 2 Materials and Methods
### Design  
Based on these regulatory and operational requirements, the RPSC was designed with a modular architecture to ensure flexibility and compliance. The architecture is structured around three main subsystems: the autopilot, the Onboard Processing Unit (OPU), and the alarm and safety system. These components exchange data in real time using MAVLink and ROS2 protocols, supporting continuous analysis and autonomous decision-making. Figure 1 illustrates this architecture, highlighting the data flows between subsystems. This architecture's modularity enables each subsystem's independent development, testing, and updating, ensuring flexibility and scalability. The design evolves from this general vision to the detailed implementation of each component, starting with the autopilot. The autopilot manages the RPSC's autonomous navigation and propulsion control. It uses a skid-steer configuration with four driven wheels. This choice optimizes maneuverability in confined spaces due to its zero-turn radius capability. Figure 2 illustrates the possible movements with this configuration. Figure 2a shows the rectilinear forward displacement, which occurs when the wheels on both sides rotate in the same direction and at the same speed, allowing the vehicle to move forward linearly. In Figure 2b, a curved trajectory is observed, resulting from the wheels on one side rotating at a higher speed than those on the opposite side; this generates a difference in angular velocity and, therefore, a smooth rotation of the robot. Figure 2c represents rotation about its own axis or in-place turning, which is achieved when the wheels on one side turn forwards and those on the opposite side turn backwards, allowing a zero turning radius and facilitating manoeuvring in confined spaces. Autonomous navigation relies on sensors that estimate the robot's state vector (position, orientation, and velocity) and detect its surroundings. Table 1 describes these components and their functions. The sensors listed in Figure 1 are integrated to provide robust navigation capabilities. Encoders enhance odometry by measuring motor rotations, enabling accurate displacement and velocity calculations. The Inertial Measurement Unit (IMU) plays a crucial role in scenarios where GNSS signals are degraded, estimating the robot's displacement based on accelerations along its axes. The magnetometer corrects accumulated errors in the trajectory estimation by providing orientation data relative to the Earth's magnetic field. For reactive navigation, ultrasonic sensors detect obstacles in real time, and algorithms dynamically  
Figure 1: RPSC high-level design. adjust the robot's trajectory based on the detected obstacles. This cohesive fusion of sensors enables the RPSC to navigate predefined routes accurately and efficiently avoid obstacles. The autopilot software must support this sensor integration, which needs to be optimised for ground vehicles. As summarised in Table 2, the software is structured in distinct modules to ensure stability, efficiency, and adaptability. These modules process real-time data from the navigation sensors. Building on the autopilot software's modular framework, the OPU acts as a high-level orchestrator, ensuring cohesive system operation by processing aggregated data and managing the parameters and states of the autopilot, safety systems, and communications. The OPU interfaces with the autopilot and sensors via Universal Asynchronous Receiver/Transmitter (UART), facilitating real-time telemetry and remote configuration.