Wireless positioning and path tracking for a mobile platform in greenhouse

Lijian Yao, Dong Hu, Chao Zhao, Zidong Yang, Zhao Zhang

Abstract


In order to realize intelligent greenhouse, an automatic navigation method for a mobile platform based on ultra-wideband (UWB) positioning technology was proposed and validated in this study. The time difference of arrival (TDOA) approach was used to monitor and track the UWB positioning to obtain the localization information of the mobile platform working in a greenhouse. After applying polynomial fitting for positioning error correction, the system accuracy was within 5 mm. A fuzzy controller model was constructed by incorporating the lateral and heading deviations as input variables and the steering angle of front wheel as the output variable. A fuzzy rule was established based on domain knowledge, as well as the steering angle of front wheel offline query table, which was applied to alleviate the calculative load of the controller. Experimental results confirmed that the automatic navigation method proposed in this study performed satisfactorily, with a steady-state error ranging from 41 mm to 79 mm when tracking straight line, and an average error of 185 mm and an average maximum error of 532 mm when tracking polygon. In addition, the maximum error occurred at the polygonal corner which could meet the needs of driving on the narrow road in the greenhouse. The method proposed in this study provides a new systematic approach for the research of greenhouse automatic navigation.
Keywords: wireless positioning, ultra-wideband, path tracking, positioning error correction, fuzzy control, query table, mobile platform, greenhouse
DOI: 10.25165/j.ijabe.20211401.5627

Citation: Yao L J, Hu D, Zhao C, Yang Z D, Zhang Z. Wireless positioning and path tracking for a mobile platform in greenhouse. Int J Agric & Biol Eng, 2021; 14(1): 216–223.

Keywords


wireless positioning, ultra-wideband, path tracking, positioning error correction, fuzzy control, query table, mobile platform, greenhouse

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References


Han X, Kim H, Moon H, Woo H, Kim J, Kim Y. Development of a path generation and tracking algorithm for a Korean auto-guidance tillage tractor. Journal of Biosystems Engineering, 2013; 38(1): 1–8.

Han X, Kim H, Kim J, Yi S, Moon H, Kim J, 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.

Ye Y, He L, Zhang Q. A robotic platform “Bin-Dog” for bin management in orchard environment. 2016 ASABE Annual International Meeting, Orlando, USA: ASABE, 2016; pp.1–8.

Ortiz B V, Balkcom K B, Duzy L, Santen E, Hartzog D L. Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations. Precision Agriculture, 2013; 14(4): 357–375.

Schmidt J F, Neuhold D, Klaue J, Schupkex D, Bettstetter C. Experimental study of UWB connectivity in industrial environment. 24th European Wireless Conference, Catania, Italy: VDE, 2018; pp.1–4.

Ahmed S N A, Zeng Y. UWB positioning accuracy and enhancements. 2017 IEEE Region 10 Conference (TENCON), Penang, Malaysia: IEEE, 2017; pp.634–638.

Su T, Gao Y. TDOA estimation of dual-satellites interference localization based on blind separation. Journal of Systems Engineering and Electronics, 2019; 30(4): 696–702.

Yun Y, Park Y, Lee B M, Hyun B, Kim Y. Distance estimation scheme exploiting IR‑UWB radar with clutter suppressing algorithm in indoor environments. Journal of Electrical Engineering & Technology, 2019(14): 1759–1769.

Amidi O. Integrated mobile robot control. International Society for Optics and Photonics, 1990; 91:504–523.

Rains G C, Faircloth A G, Thai C, Raper R L. Evaluation of a simple pure pursuit path-following algorithm for an autonomous, articulated-steer vehicle. Applied Engineering in Agriculture, 2014; 30(3): 367–374.

Ye Y, He L, Zhang Q. Steering control strategies for a four-wheel-independent-steering bin managing robot. International Federation of Automatic Control, 2016; 49(16): 39–44.

Park M W, Lee S W, Han W Y. Development of lateral control system for autonomous vehicle based on adaptive pure pursuit algorithm. 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014), Seoul, Korea: IEEE, 2014; pp.1443–1447.

Ohta H, Akai N, Takeuchi E, Kato S, Edahiro M. Pure pursuit revisited: field testing of autonomous vehicles in urban areas. 2016 IEEE 4th International Conference on Cyber-Physical Systems, Networks and Applications (CPSNA), Nagoya, Japan: IEEE, 2016; pp.7–12.

Abiyev R H, Günsel I S, Akkaya N, Aytac E, Cagman A, Abizada S. Fuzzy control of omnidirectional robot. Procedia Computer Science, 2017; 120: 608–616.

Pandey A, Sonkar R K, Pandey K K, Parhi D R. Path planning navigation of mobile robot with obstacles avoidance using fuzzy logic controller. 2014 IEEE 8th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, India: IEEE, 2014; pp.39–41.

Chen J W, Zhu H, Zhang L, Sun Y. Research on fuzzy control of path tracking for underwater vehicle based on genetic algorithm optimization. Ocean Engineering, 2018; 156: 217–223.

Hwang C L, Yang C C, Hung J Y. Path tracking of an autonomous ground vehicle with different payloads by hierarchical improved fuzzy dynamic sliding-mode control. IEEE Transactions on Fuzzy Systems, 2018; 26(2): 899–914.

Kárník J, Jakub S. Summary of available indoor location techniques. International Federation of Automatic Control, 2016; 49(25): 311–317.

Cotera P, Velazquez M, Cruz D, Medina L, Bandala M. Indoor robot positioning using an enhanced trilateration algorithm. International Journal of Advanced Robotic Systems, 2016; 13(3): 110. doi: 10.5772/63246.

Makki A, Siddig A, Saad M, Cavallaro J R, Bleakley C J. Indoor localization using time differences of arrival. IEEE Transactions on Instrumentation and Measurement, 2015; 65(3): 1–10.

Schreiber R, Bajer J. Time difference measurement algorithm for TDOA positioning system using RTL-SDR. 2017 International Conference on Military Technologies (ICMT), Brno, Czech Republic: IEEE, 2017; pp.608–612.




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