📝 Publications

• One-shot domain adaptive real-time 3D obstacle detection in farmland based on semantic-geometry-intensity fusion strategy [Available online]

  Tianhai Wang, Ning Wang, Jianxing Xiao, Yanlong Miao, Yifan Sun, Han Li, Man Zhang*

  Computers and Electronics in Agriculture, 2023 (SCI, IF_2022-2023=8.3, Special Report by WeChat Public Platform)

  

  By introducing the concept of one-shot domain adaptation, the proposed method enables 3D obstacle detection with just one sample per category. By learning the intra-category similarity and inter-category difference, the dependence on the target domain dataset is transferred to the accessible source domain dataset, which enhances the generalization of the proposed method for different scenes and categories.

• Zero-shot obstacle detection using panoramic vision in farmland [Available online]

  Tianhai Wang, Bin Chen, Ning Wang, Yuhan Ji, Han Li, Man Zhang*

  Journal of Field Robotics, 2023 (SCI, IF_2022-2023=8.3, Special Report by WeChat Public Platform)

  

  In the absence of annotated images, the current methods cannot perform optimally. Based on the visual‐semantic mapping relationship, the proposed model not only performs the correct classification of unseen obstacles, but also improves the detection performance of both seen and unseen obstacles.

• An integrated solution for collaborative scheduling of heterogeneous agricultural machines of different types in harvesting-transportation scenarios [Available online]

  Ning Wang, Zhiwen Jin, Man Zhang, Jianxing Xiao, Tianhai Wang, Qiang Sheng, Hao Wang, Han Li*

  Information Processing in Agriculture, 2025 (SCI, IF_2024-2025=7.4)

  

  Efficient coordination of machinery fleets in regional farmland operations remains a significant challenge due to the lack of scientifically grounded scheduling management strategies, high modeling complexity, and elevated operational costs. This study proposed an integrated solution for collaborative scheduling of heterogeneous agricultural machines of different types, aiming to address the collaborative scheduling of harvesters and grain trucks in harvest-transport scenarios.

• A collaborative scheduling and planning method for multiple machines in harvesting and transportation operations-Part Ⅰ: Harvester task allocation and sequence optimization [Available online]

• A collaborative scheduling and planning method for multiple machines in harvesting and transportation operations-part Ⅱ: Scheduling and planning of harvesters and grain trucks [Available online]

  Ning Wang, Shunda Li, Jianxing Xiao, Tianhai Wang, Yuxiao Han, Hao Wang, Man Zhang, Han Li*

  Computers and Electronics in Agriculture, 2025 (SCI, IF_2024-2025=8.9)

  

  In Part Ⅰ of this two-part paper, the primary focus was to address the issue of collaborative scheduling for harvesters through task allocation and whole-process path planning. In Part II, the emphasis shifts to addressing the collaborative scheduling and planning of both harvesters and grain trucks while considering the efficiency of grain trucks.

• Hybrid path planning methods for complete coverage in harvesting operation scenarios [Available online]

  Ning Wang, Zhiwen Jin, Tianhai Wang, Jianxing Xiao, Zhang Zhao, Hao Wang, Man Zhang, Han Li*

  Computers and Electronics in Agriculture, 2025 (SCI, IF_2024-2025=8.9)

  

  This study addresses the challenge of autonomous navigation path planning for achieving complete coverage operations using agricultural machines within harvest operation scenarios. We proposed a hybrid method mixing nested and spiral method to solve path planning problems for convex polygonal plots during harvest operations, focusing on the development of path planning models and complete coverage path planning (CCPP) method.

• Collaborative path planning and task allocation for multiple agricultural machines [Available online]

  Ning Wang, Xi Yang, Tianhai Wang, Jianxing Xiao, Man Zhang, Han Li*

  Computers and Electronics in Agriculture, 2023 (SCI, IF_2022-2023=8.3)

  

  The farm’s electronic map was constructed using the topological map method. The improved Dijkstra algorithm based on priority queues was combined with three different complete coverage methods: the nested method, the reciprocating method, and the combination of nested and internal spiral path methods. To solve the problem of illogical scheduling of the same type of agricultural machines, an improved ant colony method was presented based on the whole working path to minimize the path cost.

• Applications of machine vision in agricultural robot navigation: A review [Available online]

  Tianhai Wang, Bin Chen, Zhenqian Zhang, Han Li, Man Zhang*

  Computers and Electronics in Agriculture, 2022 (SCI, IF_2022-2023=8.3, ESI Highly Cited Paper, Cited by 100+, Special Report by WeChat Public Platform)

• Research Progress of Agricultural Robot Full Coverage Operation Planning [Available online]

  Ning Wang, Yuxiao Han, Yaxuan Wang, Tianhai Wang, Man Zhang, Han Li*

  Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery, 2022 (EI)

• Applications of UAS in Crop Biomass Monitoring: A Review [Available online]

  Tianhai Wang, Yadong Liu, Minghui Wang, Qing Fan, Hongkun Tian, Xi Qiao*, Yanzhou Li*

  Frontiers in Plant Science, 2021 (SCI, IF_2021-2022=6.627)

• Computer vision technology in agricultural automation —A review [Available online]

  Hongkun Tian, Tianhai Wang, Yadong Liu, Xi Qiao*, Yanzhou Li*

  Information Processing in Agriculture, 2020 (EI, Cited by 500+)