Review of current robotic approaches for weed management in paddy cultivation

Weed management remains a critical component of sustainable rice production; however, traditional methods, such as manual and chemical weeding, present significant economic, environmental, and health-related concerns. This review systematically examines recent advancements in robotic weed management technologies specifically developed for paddy cultivation, as well as those with potential applicability in such environments. It explores the integration of mechanical, chemical, and laser-based weeding mechanisms with advanced imaging systems, sensor technologies, artificial intelligence-based algorithms, and robotic navigation. Autonomous platforms employing technologies such as Variable Rate Technology (VRT), Global Navigation Satellite System (GNSS), Site-Specific Weed Management (SSWM), deep learning algorithms, and LiDAR significantly enhance weed detection accuracy, reducing chemical usage and labor dependency. Despite these advancements, several challenges, which include high initial costs, limited adaptability to different weed species, technical complexities in operating effectively in diverse environmental conditions in paddy fields, infrastructure challenges, and socio-cultural resistance, hinder widespread adoption of robotic weed management in paddy cultivation. This review addresses these knowledge gaps by critically evaluating the technological limitations of current robotic platforms and identifying areas that require further research, such as terrain adaptability, long-term ecological impacts, and AI-based weed identification in complex environments. By providing a comprehensive analysis of the current landscape, this article aims to inform and guide future research and development efforts toward creating efficient, scalable, and sustainable robotic weed management solutions for global paddy cultivation. • Rice farming requires effective weed management to maintain economic viability. • Conventional methods like manual, mechanical and chemical weeding have drawbacks. • Robotic weed management shows great potential to revolutionize rice farming. • Robotic weeders improve efficiency and sustainability of rice farming practices.