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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #334284

Research Project: Sensing Technologies for the Detection and Characterization of Microbial, Chemical, and Biological Contaminants in Foods

Location: Environmental Microbial & Food Safety Laboratory

Title: Development of PID and fuzzy control strategies for navigation in agricultural environments

item BONADIES, STEPHANIE - University Of Maryland
item SMITH, NEAL - University Of Maryland
item NIEWOEHNER, NATHAN - University Of Maryland
item LEE, ANDREW - University Of Maryland
item Lefcourt, Alan
item GADSDEN, ANDREW - University Of Maryland

Submitted to: Journal of Dynamic Systems, Measurement, and Control
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/22/2017
Publication Date: 6/1/2018
Citation: Bonadies, S., Smith, N., Niewoehner, N., Lee, A.S., Lefcourt, A.M., Gadsden, A. 2018. Development of PID and fuzzy control strategies for navigation in agricultural environments. Journal of Dynamic Systems, Measurement, and Control. 140(6):061007.

Interpretive Summary: Use of robotic vehicles in crop production has the potential to reduce agricultural labor costs. This paper examines two different methods for controlling the motion of a robotic vehicle as it progresses down a crop row. The two methods use PID or Fuzzy Logic controllers, respectively. Image data from the robotic vehicle was used to guide the vehicle down a test course. Results for both control methods were similar, and either method should perform adequately in field use. This manuscript will be of interest to agricultural and mechanical engineers, agricultural equipment manufactures, food production companies, and farmers.

Technical Abstract: Farming and agriculture is an area that may benefit from improved use of automation in order to increase working hours and improve food quality and safety. In this paper, a commercial robot was purchased and modified, and crop row navigational software was developed, to allow the ground-based robot to autonomously navigate a crop row setting. A proportional-integral-derivative (PID) controller and a fuzzy-logic controller were developed to compare the efficacy of each controller based on which controller navigated the crop row more reliably. Results of the testing indicate that both controllers perform well, with some differences depending on the scenario.