Abstract

We consider the problem of multirobot routing in vineyards, a task motivated by our ongoing project aiming at creating a corobotic system to implement precision irrigation on large-scale commercial vineyards. The problem is related to a combinatorial optimization problem on graphs called “team orienteering.” Team orienteering is known to be NP-hard, thus motivating the development of heuristic solutions that can scale to large problem instances. We propose three different parameter-free approaches informed by the domain we consider and compare them against a general purpose heuristic developed previously. In numerous benchmarks derived from data gathered in a commercial vineyard, we demonstrate that our solutions outperform the general purpose heuristic and are scalable, thus allowing us to solve instances with tens of thousands of vertices in the graphs. Note to Practitioners —Routing problems with budget and motion constraints are pervasive to many applications. In particular, the structural constraints considered in this problem are found not only in agricultural environments but also in warehouse logistics and other domains where goods are arranged along regular linear structures. This article proposes and analyzes algorithms that can be applied when multiple agents must be coordinated in these environments. In particular, by utilizing domain-specific knowledge, the solutions proposed in this article outperform general purpose approaches that poorly scale with the size of the environment. The algorithms we present also ensure that no collisions occur between robots—an aspect normally neglected in algorithms previously proposed to solve the team orienteering problem.

Highlights

  • W INE grapes are ideally grown following a stress irrigation regime, that is, each vine receives a limited amountManuscript received June 1, 2019; revised February 24, 2020; accepted February 28, 2020

  • The algorithms we present ensure that no collisions occur between robots—an aspect normally neglected in algorithms previously proposed to solve the team orienteering problem

  • In [2], we presented a portable emitter actuation device (PEAD), that is, an actuator that can be used to latch and adjust a variable rate emitter, and in [3] we showed how this concept can be extended for mounting on a robotic arm

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Summary

INTRODUCTION

W INE grapes are ideally grown following a stress irrigation regime, that is, each vine receives a limited amount. Findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S Department of Agriculture or the National Science Foundation. Delivering “the right amount of water” is the main objective of precision irrigation and remains an open challenge, especially in large-scale commercial vineyards. This problem is acute in California, where wine grape production has a significant economic impact, but freshwater availability is limited. In development by the University of California, robotassisted precision irrigation delivery (RAPID) is a scalable irrigation management solution that aims to assist vine growers with water conservation efforts while preserving yield and quality.

RELATED WORK
Orienteering Problem
Robots in Agriculture
PROBLEM DEFINITION
HEURISTICS FOR THE IGTOP PROBLEM
Single Agent GPR Heuristic
18: Append path from current vertex to ending vertex to tour
Vineyard Sectioning
Series GPR
25: Add vertices and times to con f li ctmap
Parallel GPR
Guided Local Search
32: Tell tourM to save more time for the end
EXPERIMENTAL COMPARISON
Findings
CONCLUSION AND FUTURE WORK

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