农业机械学报2026，Vol.57Issue(5)：1-18,18.DOI:10.6041/j.issn.1000-1298.2026.05.001
果蔬采摘机器人避障作业技术研究进展综述
Advances and Trends in Obstacle Avoidance Operation Technologies for Fruit and Vegetable Harvesting Robots
摘要
Abstract
Harvesting robots represent a critical enabling technology for advancing the mechanization and automation of fruit and vegetable harvesting and have become a prominent research focus within the global agricultural robotics community.Unlike structured industrial environments,agricultural harvesting tasks are performed in highly unstructured and dynamic settings,where fruits,branches,and leaves are densely intertwined and frequently occluded one another.As a result,obstacle-aware operation capability has emerged as a key technological bottleneck that fundamentally limits the overall performance,robustness,and practical applicability of fruit and vegetable harvesting robots.In this context,a comprehensive review of recent advances in obstacle-avoidance technologies for harvesting robots operating in complex agricultural environments was provided.The review was structured around four core aspects that were critical to obstacle-aware harvesting:target perception,manipulation decision-making,servo control,and end-effector and execution structures.Firstly,advances in visual and multimodal perception methods for detecting and segmenting fruits,branches,and foliage under occlusion were examined,with particular attention paid to deep learning-based approaches and three-dimensional sensing techniques.Secondly,manipulation decision-making strategies,including motion planning,behavior selection,and learning-based decision models,were reviewed with respect to their ability to cope with high-dimensional constraints and environmental uncertainty.Thirdly,servo control methods for harvesting robots were discussed,focusing on visual servoing,force-aware control,and adaptive strategies that enabled precise and safe manipulation in cluttered scenes.Finally,the design of execution mechanisms and end-effectors was analyzed,highlighting how mechanical structure,compliance,and functional integration influence obstacle avoidance performance during harvesting operations.Based on this review,it was further analyzed and summarized the major technical challenges faced by obstacle-aware harvesting robots in real-world agricultural scenarios.These challenges included limited perception reliability under severe occlusion,insufficient generalization of decision and control strategies across varying crop types and growth stages,difficulties in reproducing human harvesting skills,and the lack of coordination between robotic system design and agricultural production practices.Finally,future research trends were discussed,emphasizing the potential of embodied intelligence,end-to-end learning frameworks,and the integration of agronomic knowledge with robotic design.With advancements in factory-based agronomic management,artificial intelligence,and robotic technologies,the development of embodied intelligence-particularly supported by multimodal information perception and environmental interactive learning,and backed by China's intelligent robotics industry would serve as a crucial technical pathway for enhancing the capability of agricultural robots in handling complex operational tasks.关键词
采摘机器人/避障作业/主动感知/运动规划Key words
harvesting robot/obstacle-avoidance operation/active perception/motion planning分类
信息技术与安全科学引用本文复制引用
冯青春,陈立平,陈辰,洪志超,许宝成,赵春江..果蔬采摘机器人避障作业技术研究进展综述[J].农业机械学报,2026,57(5):1-18,18.基金项目
国家自然科学基金项目(32572207)和北京市农林科学院创新能力建设专项与预探索项目(TSXM202514) （32572207）
