Autonomous Combine Harvesters: A Scoping Review of Operational Reliability and Application Feasibility

Autonomous combine harvesters may improve harvesting timeliness, reduce labor dependence, and support data-driven grain production, but deployment depends on whether they can complete harvesting missions reliably under variable soil–crop–machine interactions and at acceptable lifecycle cost. This scoping review was reported in accordance with PRISMA 2020 and PRISMA-ScR. The Web of Science Core Collection was searched for English-language peer-reviewed publications from 2006 to 30 May 2026, supplemented by backward reference screening and forward citation tracking. Of 281 records identified, 138 studies were included in a framework-based thematic synthesis. Representative platforms and enabling technologies were compared, the reviewed studies were descriptively grouped according to their reported validation settings, reliability was assessed at component, system, and mission levels, and feasibility was examined across economic, operational, infrastructural, regulatory, and organizational dimensions. The evidence shows progress in positioning, navigation, crop-boundary recognition, speed regulation, component monitoring, fault diagnosis, and remote supervision, but repeated long-duration validation of complete autonomous harvesting missions remains limited. Current evidence therefore supports function-specific automation and supervised autonomy more strongly than unrestricted driverless operation. Future research should prioritize bounded operating domains, graceful degradation, standardized safety assessment, multi-scenario field validation, and reliable single-machine autonomy before fleet-level deployment.