Auto-steering based precise coordination method for in-field multi-operation of farm machinery

Jie Wang, Yuting Zhu, Zhibo Chen, Lili Yang, Caicong Wu

Abstract


Multi-operation within a field and multi-machinery within a machinery operation are common in the scene of scaled farm machinery service, especially with soaring usage of automated steering system in small and medium machinery cooperatives. The object of this study was to explore a precise and efficient in-field coordination method to realize flow-shop scheduling for farm machinery fleet equipped with RTK-GNSS based auto-steering system. The new method is based on three-dimensional coordinate system (XYZ), within which the concept of field, operation strip, and operation task were defined. Under this concept framework, the operation strip state was further defined and its updating algorithm was designed, which can be used for optimization simulations and experiments. To evaluate the method, the waiting time between simulation and a real-world case was compared, and one cloud based prototype system was developed to demonstrate the practicability in the field by using NX200+ automated steering system. The simulations showed that the in-field coordination can shorten the waiting time between two adjacent operations. The waiting time between rotary hoeing and seeding can be shortened from 4 h to 6.3 min. The field experiment showed that the prototype system could keep good consistency of ridges for a fleet by sharing the guidance line.
Keywords: GNSS, auto-steering system, in-field coordination operation, farm machinery, method, simulation
DOI: 10.25165/j.ijabe.20181105.3827

Citation: Wang J, Zhu Y T, Chen Z B, Yang L L, Wu C C. Auto-steering based precise coordination method for in-field multi-operation of farm machinery. Int J Agric & Biol Eng, 2018; 11(5): 174–181.

Keywords


GNSS, auto-steering system, in-field coordination operation, farm machinery, method, simulation

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References


Rovira-Más F, Chatterjee I, Sáiz-Rubio V. The role of GNSS in the navigation strategies of cost-effective agricultural robots. Computers and Electronics in Agriculture, 2015; 112: 172–183.

Bechar A, Vigneault C. Agricultural robots for field operations. Part 2: Operations and systems. Biosystems Engineering, 2017; 153: 110–128.

Carballido J, Perez-Ruiz M, Emmi L, Aguera J. Comparison of positional accuracy between rtk and RTX GNSS based on the autonomous agricultural vehicles under field conditions. Applied Engineering in Agriculture, 2014; 30(3): 361–366.

Ming L, Imou K, Wakabayashi K, Yokoyama S. Review of research on agricultural vehicle autonomous guidance. Int J Agric & Biol Eng, 2009; 2(3): 1–16.

Han X, Kim H-J, Jeon C W, Moon H C, Kim J H. Development of a low-cost GPS/INS integrated system for tractor automatic navigation. Int J Agric & Biol Eng, 2017; 10(2): 123–131.

Hu J, Gao L, Bai X, Li T, Liu X. Review of research on automatic guidance of agricultural vehicles. Transactions of the CSAE, 2015; 31(10): 1–10. (in Chinese)

Ji C, Zhou J. Current situation of navigation technologies for agricultural machinery. Transactions of the CSAM, 2014; 45(9): 44–54. (in Chinese)

[8] Bochtis D D, Sørensen C G C, Busato P. Advances in agricultural machinery management: A review. Biosystems Engineering, 2014; 126: 69–81.

Conesa-Munoz J, Gonzalez-De-Soto M, Gonzalez-De-Santos P, Ribeiro A. Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks. Sensors, 2015; 15(3): 5402–5428.

Senlin G, Nakamura M, Shikanai T, Okazaki T. Hybrid petri nets modeling for farm work flow. Computers and Electronics in Agriculture, 2008; 62(2): 149–158.

Bochtis D D, Dogoulis P, Busato P, Sørensen C G, Berruto R, Gemtos T. A flow-shop problem formulation of biomass handling operations scheduling. Computers and Electronics in Agriculture, 2013; 91: 49–56.

Wu C. Time-windows based temporal and spatial scheduling model for agricultural machinery resources. Transactions of the CSAM, 2013; 44(5): 237–241, 231. (in Chinese)

Valentinov V. Why are cooperatives important in agriculture? An organizational economics perspective. Journal of Institutional Economics, 2007; 3(1): 55.

Balta H, Bedkowski J, Govindaraj S, Majek K, Musialik P, Serrano D, et al. Integrated data management for a fleet of search-and-rescue robots. Journal of Field Robotics, 2017; 34(3): 539–582.

Fountas S, Carli G, Sørensen C G, Tsiropoulos Z, Cavalaris C, Vatsanidou A, et al. Farm management information systems: Current situation and future perspectives. Computers and Electronics in Agriculture, 2015; 115: 40–50.

Sørensen C G, Bochtis D D. Conceptual model of fleet management in agriculture. Biosystems Engineering, 2010; 105(1): 41–50.

Bochtis D D, Sørensen C G, Vougioukas S G. Path planning for in-field navigation-aiding of service units. Computers and Electronics in Agriculture, 2010; 74(1): 80–90.

Gutman P O, Ioslovich I. Inter-field routes scheduling and rescheduling for an autonomous tractor fleet at the farm. International Conference on Methods and MODELS in Automation and Robotics, IEEE, 2013; pp.812–817.

Bochtis D D, Sørensen C G. The vehicle routing problem in field logistics part I. Biosystems Engineering, 2009; 104(4): 447–457.

Bochtis D D, Sørensen C G. The vehicle routing problem in field logistics: Part II. Biosystems Engineering, 2010; 105(2): 180–188.

Bochtis D D, Vougioukas S G. Minimising the non-working distance travelled by machines operating in a headland field pattern. Biosystems Engineering, 2008; 101(1): 1–12.

Bochtis D, Vougioukas S, Griepentrog H W. A mission planner for an autonomous tractor. Transactions of the ASABE, 2009; 52(5): 1429–1440.

Noguchi N, Will J, Reid J, Zhang Q. Development of a master–slave robot system for farm operations. Computers and Electronics in Agriculture, 2004; 44(1): 1–19.

Noguchi N, Will J, Ishii K, Reid J. Development of master-slave robot system-obstacle avoidance algorithm. Proceedings of the Conference on Automation Technology for Off-Road Equipment, ASABE, 2002. doi: 10.13031/2013.10065.

Zhang C, Noguchi N, Yang L. Leader–follower system using two robot tractors to improve work efficiency. Computers and Electronics in Agriculture, 2016; 121: 269–281.

Zhang L, Ahamed T, Zhang Y, Gao P, Takigawa T. Vision-based leader vehicle trajectory tracking for multiple agricultural vehicles. Sensors, 2016; 16(4): 578. doi: 10.3390/s16040578

Auat Cheein F A, Scaglia G, Torres-Torriti M, Guivant J, Javier Prado A, Arno J, et al. Algebraic path tracking to aid the manual harvesting of olives using an automated service unit. Biosystems Engineering, 2016; 142: 117–132.

Wu C C, Zhou L, Wang J, Cai Y P. Smartphone based precise monitoring method for farm operation. Int J Agric & Biol Eng, 2016; 9(3): 111–121.

Orfanou A, Busato P, Bochtis D D, Edwards G, Pavlou D, Sorensen C G, et al. Scheduling for machinery fleets in biomass multiple-field operations. Computers and Electronics in Agriculture, 2013; 94: 12–19.

Han X Z, Kim H J, Kim J Y, Yi S Y, Moon H C, Kim J H, et al. Path-tracking simulation and field tests for an auto-guidance tillage tractor for a paddy field. Computers and Electronics in Agriculture, 2015; 112: 161–171.

Zhou K, Leck Jensen A, Sorensen C G, Busato P, Bothtis D D. Agricultural operations planning in fields with multiple obstacle areas. Computers and Electronics in Agriculture, 2014; 109: 12–22.

Jensen M A F, Bochtis D, Sørensen C G, Blas M R, Lykkegaard K L. In-field and inter-field path planning for agricultural transport units. Computers and Industrial Engineering, 2012; 63(4): 1054–1061.

Han X Z, Kim H-J, Moon H-C, Kang Y-S, Kim J-H, Kim Y-J. Development of path generation algorithms for Korean auto-guidance tillage tractor. ASABE Annual International Meeting, Dallas, Texas, July 29 - August 1, 2012; pp.4723–4732.

Hu J, Li T. Cascaded navigation control for agricultural vehicles tracking straight paths. Int J Agric & Biol Eng, 2014; 7(1): 36–44.

Wang L, Ni Y, Chang Y, Cui R, Liu Y. Research on integrity of ground-based augmentation system under GPS/BDS constellations environment. Computer Engineering, 2015; 41(12): 30–35.




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