Research on kiwifruit harvesting robot worldwide: A solution for sustainable development of kiwifruit industry
Open accessAbstract
Kiwifruit harvesting is labor-intensive, and social issues like an aging population and a declining agricultural workforce have significantly increased costs, presenting unprecedented challenges to the industry. Automatic harvesting systems utilizing multi-sensor fusion, AI, and automation technologies show great potential for replacing manual labor in kiwi harvesting. This paper reviews over 140 research articles related to kiwi fruit harvesting robots, summarizing existing progress in two key areas: target fruit recognition and positioning systems, and fruit picking and collection systems. We compare the pros and cons of various methods, including traditional image recognition and deep learning, active and passive localization techniques, diverse end-effector design structure and driving mechanisms, robotic arm path planning, and harvesting systems. The results show that challenges remain in the commercialization of kiwi harvesting robots. The absence of a unified evaluation standard for robot performance makes the latest research achievements hard to be inherited, leading to slow advancements. Current algorithms are often not lightweight enough for low-cost embedded systems. Additionally, the reliance on manual labeling of dense targets and the accumulation of system error compromise the robustness of target recognition and spatial positioning in open environments. The existing studies tend to focus on local improvements rather than the entire harvesting system. So address…
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Dual or multiple actuator configurations with a 2:1 redundancy ratio maintain capacity during faults, as demonstrated in manufacturing human-robot collaboration and agricultural systems.
“For instance, dual or multiple actuator configurations with a 2:1 redundancy ratio maintain capacity during faults, as demonstrated in manufacturing HRC with reduced downtime [35] and agricultural systems with reliable uptime [9].”
From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [9]
Fault-tolerant cooperative robotics faces significant barriers in scalability, computational complexity, and real-world validation.
“Fault-tolerant cooperative robotics faces significant barriers in scalability, computational complexity, and real-world validation, as highlighted across the literature.”
From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [9]
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Self-citation
- Authors
- Tian, Z., Guo, X., Ma, W., & Xue, X.
- Affiliations
- Zhejiang University (CN)
- Chinese Academy of Agricultural Sciences (CN)
- Nanjing Institute of Agricultural Mechanization (CN)
- Corresponding author
- Ma, Wei
- Xue, Xinyu
- Venue
- Smart Agricultural Technology
- Publisher
- Elsevier BV
- Published
- 2025-03
- Volume
- 10
- Pages
- 100792
- ISSN
- 2772-3755 (ISSN-L)
- OpenAlex
- W4406596370
- Cited by
- 7
- References
- 50
- Citations by year
- 2026: 2 · 2025: 5
- FWCI
- 3.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Smart Agricultural Technology (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Chinese Academy of Agricultural Sciences
- Central Public-interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences (S2023009)
- Sichuan Provincial Science and Technology Support Program (2023JDRC0132)
- Agricultural Science and Technology Innovation Program (ASTIP2024-34-IUA-10)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Physical Sciences › Engineering › Mechanical Engineering › Agricultural Engineering and Mechanization
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Keywords
- fruit detection, fruit localization, fruit harvesting, robotic arm path planning, multi-sensor fusion, embedded systems, agricultural labor shortage
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