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Research Papers

Task Assignment and Trajectory Planning Algorithm for a Class of Cooperative Agricultural Robots

[+] Author and Article Information
Ni Li, Charles Remeikas

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816

Yunjun Xu

Associate Professor
Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: yunjun.xu@ucf.edu

Suhada Jayasuriya

Department of Mechanical
Engineering and Mechanics,
Drexel University,
Philadelphia, PA 19104

Reza Ehsani

Citrus Research and Education Center,
University of Florida,
Lake Alfred, FL 33850

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 26, 2013; final manuscript received October 15, 2014; published online December 10, 2014. Assoc. Editor: Sergey Nersesov.

J. Dyn. Sys., Meas., Control 137(5), 051004 (May 01, 2015) (9 pages) Paper No: DS-13-1326; doi: 10.1115/1.4028849 History: Received August 26, 2013; Revised October 15, 2014; Online December 10, 2014

Agricultural field operations, such as harvesting for fruits and scouting for disease, are labor intensive and time consuming. With the recent push toward autonomous farming, a method to rapidly generate trajectories for a group of cooperative agricultural robots becomes necessary. The challenging aspect of solving this problem is to satisfy realistic constraints such as changing environments, actuation limitations, nonlinear heterogeneous dynamics, conflict resolution, and formation reconfigurations. In this paper, a hierarchical decision making and trajectory planning method is studied for a group of agricultural robots cooperatively conducting certain farming task such as citrus harvesting. Within the algorithm framework, there are two main parts (cooperative level and individual level): (1) in the cooperative level, once a discrete reconfiguration event is confirmed and replanning is triggered, all the possible formation configurations and associated robot locations for specific farming tasks will be evaluated and ranked according to the feasibility condition and the cooperative level performance index; and (2) in the individual level, a local pursuit (LP) strategy based cooperative trajectory planning algorithm is designed to generate local optimal cooperative trajectories for agricultural robots to achieve and maintain their desired operation formation in a decentralized manner. The capabilities of the proposed method are demonstrated in a citrus harvesting problem.

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Figures

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Fig. 1

Algorithm architecture

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Fig. 2

Citrus orchard layout used in the simulation

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Fig. 3

Three available formation configuration options in the simulation

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Fig. 4

Generated trajectories for the followers and virtual leader in phases 1 through 7. (a) Phase 1 through phase 4 and (b) phase 5 through phase 7.

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Fig. 5

Followers’ speed profiles during phase 1

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Fig. 6

Followers’ heading angle profiles during phase 1

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Fig. 7

Followers’ SCP profiles during phase 1

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Fig. 8

Followers’ bias profiles in the x-direction and y-direction during phase 1

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Fig. 9

Agricultural robots’ control profiles during phase 1. (a) Tire frictional force Fi,xf,k2+Fi,yf,k2 and (b) aerodynamic resistance force Fi,yr,kin the lateral direction.

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