A Comprehensive Review of Research and Applications of Intelligent Manipulators in Agriculture

Agricultural intelligent manipulators are essential for autonomous operations in smart agriculture. However, their industrial deployment faces critical bottlenecks, including perception failures, crop damage, and poor cost–benefit ratios in unstructured environments. Following the PRISMA guidelines, this study reviewed 22 key representative studies and 78 related studies (2015–2026). This review analyzes mechanisms for low-damage and high-precision operations across hardware (rigid–flexible structures), perception (multi-modal fusion), and decision-making (intelligent control). We compare operational efficiency and damage rates in harvesting, transplanting, and sorting, finding that rigid–flexible actuators with vision-guided force control are key to overcoming current limitations. To evaluate these technologies, we established a benchmarking framework across fruit/vegetable harvesting, seedling grafting, and precision plant protection to assess four technological trajectories. We also address engineering challenges: machinery–agronomy misalignment, high sensor costs, and limited edge computing. Notably, we introduce an economic payback period analysis to evaluate commercial feasibility. Ultimately, future research should prioritize lightweight variable-stiffness hardware, synchronous visuo-tactile perception, and digital twins to seamlessly integrate machinery and agronomy.