Developing off-highway autonomy presents two concepts of automation in off-highway machines. The first shows how modular controls, kinematic sensing and AI-driven angle detection can move machines from basic assistance functions toward higher levels of automation. The second focuses on the application of next-generation hardware to improve machine safety. The presentation highlights current challenges in sensor fusion and machine variability, then shows how targeted AI models can reduce commissioning effort and speed deployment. It closes by connecting next-generation hardware, perception and radar-based collision avoidance to safer, more productive off-highway machines.

• How modular controls, advanced sensing and AI-driven angle detection can support the transition from assistance functions to higher-level automation
• Key autonomy challenges, including sensor fusion, machine variability and deployment complexity
• How next-generation hardware, perception and radar-based collision avoidance can improve safety