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Lei et al. Intell Robot 2022;2(4):313­32 Intelligence & Robotics
DOI: 10.20517/ir.2022.18

Research Article Open Access

An informative planning-based multi-layer robot navi-

gation system as applied in a poultry barn

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Tingjun Lei , Guoming Li 2,3 , Chaomin Luo , Li Zhang , Lantao Liu , Richard Stephen Gates 2,3,6
1 Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA.
2 Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA.
3 Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
4 Department of Poultry Science, Mississippi State University, Mississippi State, MS 39762, USA.
5 Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47408, USA.
6 Egg Industry Center, Iowa State University, Ames, IA 50011, USA.
Correspondence to: Prof. Chaomin Luo, Department of Electrical and Computer Engineering, Mississippi State University, 406
Hardy Road, Mississippi State, MS 39762, USA. E-mail: Chaomin.Luo@ece.msstate.edu; ORCID: 0000-0002-7578-3631
How to cite this article: Lei T, Li G, Luo C, Zhang L, Liu L, Gates RS. An informative planning-based multi-layer robot navigation
system as applied in a poultry barn. Intell Robot 2022;2(4):313-32. http://dx.doi.org/10.20517/ir.2022.18.
Received: 10 Jun 2022 First Decision: 29 Jul 2022 Revised: 13 Aug 2022 Accepted: 25 Aug 2022 Published: 12 Oct 2022

Academic Editor: Simon X. Yang Copy Editor: Jia-Xin Zhang Production Editor: Jia-Xin Zhang

Abstract
Many real-world robot applications, as found in precision agriculture, poultry farms, disaster response, and environ-
ment monitoring, require search, locate, and removal (SLR) operations by autonomous mobile robots. In such appli-
cation settings, the robots initially search and explore the entire workspace to find the targets, so that the subsequent
robots conveniently move directly to the targets to fulfill the task. A multi-layer robot navigation system is necessary
for SLR operations. The scenario of interest is the removal of broiler mortality by autonomous robots in poultry barns
in this paper. Daily manual collection of broiler mortality is time- and labor-consuming, and an autonomous robotic
system can solve this issue effectively. In this paper, a multi-layer navigation system is developed to detect and re-
move broiler mortality with two robots. One robot is assigned to search a large-scale workspace in a coverage mode
and find and locate objects, whereas the second robot directly moves to the located targets to remove the objects.
Directed coverage path planning (DCPP) fused with an informative planning protocol (IPP) is proposed to efficiently
search the entire workspace. IPP is proposed for coverage directions in DCPP devoted to rapidly achieving spatial
coverage with the least estimation uncertainty in the decomposed grids. The detection robot consists of a developed
informative-based directed coverage path planner and a You Only Look Once (YOLO) V4-based dead bird detector.
It refines and optimizes the coverage path based on historical data on broiler mortality distribution in a broiler barn.
The removal robot collects dead broilers driven by a new hub-based multi-target path routing (HMTR) scheme, which
is applicable to row-based environments. The proposed methods show great potential to navigate in broiler barns ef-

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar­
ing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you
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