As off-highway equipment evolves toward higher levels of automation, reliable perception in harsh, unpredictable environments remains one of the industry’s most significant challenges. Dust, fog, rain, darkness, vibration and glare routinely degrade traditional sensing approaches, making consistent real time decision-making difficult. This session explores how edge level sensor fusion – combining AI-based vision with industrial radar – creates a robust, machine-ready perception layer that enables safer, more productive and increasingly autonomous mobile equipment. Key takeaway: robust autonomy starts at the edge – where sensor fusion happens closest to the machine, designed for real equipment, real worksites and real operating conditions.

• How edge fused AI vision and radar enable collision avoidance, automatic braking and intelligent speed control, while reducing false positives
• How fused perception data becomes a valuable digital asset, supporting event logging, simulation, fleet analytics and continuous AI improvement
• How this architecture aligns with software-defined vehicle strategies, leveraging CAN and ethernet interfaces for updates and long-term scalability