Agricultural Mobile Platforms for Smart Farming: Design Requirements, Platform Types, Applications, and Future Perspectives
Agricultural mobile platforms provide the physical foundation for sensing, field operations, and material handling in smart farming, yet their design is strongly constrained by crop geometry, terrain conditions, task-specific payloads, energy demand, and operational reliability. This review examines agricultural mobile platforms from four complementary perspectives: design and operational requirements, platform classification, powertrain and mobility technologies, and agricultural applications. Wheeled, tracked, legged and wheel-legged, and rail-guided or constrained-motion platforms are compared in terms of mobility characteristics and suitable operating environments. Power sources, drive systems, steering mechanisms, mobility control, and platform–implement integration are further discussed, with particular attention to electrification, distributed drive, dynamic loads, and coordinated power allocation. Representative applications include crop monitoring and phenotyping, precision crop management, weeding and harvesting, and transportation and multi-purpose operations. Current challenges arise from the strong coupling among terrain adaptability, payload, energy capacity, autonomy, and long-term reliability, as well as limited interoperability between platforms and implements. Future development should emphasize task-oriented reconfigurable platforms, standardized mechanical and electrical interfaces, task-level energy management, and mobility control that accounts for real-time platform and terrain conditions.
Authors
- Huihui Sun (ORCID: https://orcid.org/0000-0002-5373-3879)
- Rui-Feng Wang (ORCID: https://orcid.org/0009-0004-9051-0094)
- Xing Zhang (ORCID: https://orcid.org/0000-0003-2447-1408)
- Fan Guo
Institutions
- University of Georgia (US)
- Tsinghua Sichuan Energy Internet Research Institute (CN)
- Huainan Normal University (CN)
- Anhui Polytechnic University (CN)
- Zhejiang University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Agriculture
- Published
- 2026-09-13
- DOI
- https://doi.org/10.3390/agriculture16181960
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00