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PUBLISHED DATE: - 28-09-2024
DOI: -
https://doi.org/10.37547/tajabe/Volume06Issue09-04
PAGE NO.: - 15-34
ROBOTICS APPLICATION IN POULTRY
FARMING: PROBLEMS AND PROSPECTS
Etop Nkereuwem Essien (PhD)
Department of Agricultural Education, University of Uyo, Nigeria
Inibehe Archibong Job (PhD)
Department of Agricultural Education, University of Uyo, Nigeria
INTRODUCTION
In the modern era of Information and Technology,
gadgets and electronic devices are now inevitable
in our day-to-day life. Technology helps in routine
activities in a well-organized manner and move
forward at ease. Activities such as poultry farming
is not left out. Poultry farming plays a crucial role
in meeting the growing demand for affordable and
safe food products (Sarıca et al., 2018). Poultry
production is cost-effective (Ahmad et al., 2022; de
Mesquita Souza Saraiva et al., 2022) and offers
high-quality proteins (Attia et al., 2022; de
Mesquita Souza Saraiva et al., 2022). Furthermore,
it contributes to economic and social sustainability
by creating favourable investment opportunities
for producers (Rodi
ć et al., 2011). Nevertheless,
modern poultry farming faces challenges, including
animal health and welfare, poultry house
management, production, and human-induced
issues, which are critical for sustainability in
poultry farming (Gunnarsson et al., 2020; Hafez
and Attia, 2020). Poultry farming management is
transitioning from human labour to smart systems
facilitated by machines (Ren et al., 2020). The
application of smart technologies in poultry
farming is expected to enable faster and more
effective farm and animal monitoring, leading to
better-informed decision-making through the
evaluation of extensive data (Sharma and Patil,
2018).
Among the various technological tools, robots are
emerging as a prominent solution in poultry
farming, serving diverse functions such as
phenotyping, monitoring, management, and
environmental control (Sahoo et al., 2022).
RESEARCH ARTICLE
Open Access
Abstract
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Recently, functional robots have been developed in
poultry farming that can perform specific tasks
–
such as collecting floor eggs and dead birds, thus
saving labour and facilitating the production (Astill
et al., 2020; Wu et al., 2022; Zhao, 2021). However,
research on the impact of robots designed for
direct contact with animals on animal health and
welfare is limited (Dennis et al., 2020; Parajuli et al.,
2020). Additionally, robots have shown potential in
studying collective and social behaviour through
interaction with animals, with robot-animal
interaction presenting a promising research area
(Gribovskiy et al., 2018). Such studies are inspired
by the rapid social attachment mechanism known
as filial imprinting observed in young animals
(Vallortigara and Versace, 2022). Robots
interacting with animals hold a huge potential in
the investigation of social behaviour and
ethological research because they enable highly
standardized,
controlled,
replicable
and
reproducible
experimental
designs.
This
innovative approach allows to explore complex
social dynamics in various species (Romano et al.,
2019).
There is growing interest in robotics for poultry
farming. Previous work has explored the potential
impact of smart technology in the poultry industry,
focusing
on
robotics,
advanced
sensors,
automation technology, AI (Artificial Intelligence),
big data analysis, internet of things, and
transportation (Abbas, 2022; Park et al., 2022; Ren
et al., 2020; Wu et al., 2022). Robot-animal social
interactions and the impact of robots on animal
welfare and animal behaviour in poultry had
limited coverage.
Challenges in Poultry Farming
Animal health and welfare
: Ensuring animal
health is crucial in poultry farms. Poultry diseases
pose a significant threat, as some of them have the
potential to escalate into pandemics with far-
reaching global consequences (Carenzi and Verga,
2009). To mitigate such risks, continuous
monitoring of poultry is essential for disease
prevention, biosecurity measures, early diagnosis,
and timely treatment (Pearce et al., 2023).
Upholding animal welfare (Webster et al., 2005)
and “life worth living” (Mellor et al., 2016) while
ensuring sustainable production practices (Yang et
al., 2020) is another challenge. To achieve a
comprehensive assessment of animal welfare,
standardized parameters must be established and
accurately monitored (Wemelsfelder and Mullan,
2014). The evaluation of animal welfare revolves
around indicators such as proper nutrition, good
health, suitable housing, and appropriate
behaviour (Paul et al., 2022). To evaluate animal
welfare, it is fundamental to understand the
natural behaviour of a poultry species (Putyora et
al., 2023), including social behaviour.
Poultry house management
: Among livestock
systems, poultry systems are considered
environmentally friendly, because produce low
greenhouse gas emissions (Leinonen and
Kyriazakis, 2016; Vries and Boer, 2010) and lower
water usage (Gerber et al., 2015; Vaarst et al.,
2015). However, they still require special attention
to their environmental impact, particularly
concerning issues such as ammonia release and
nitrate leaching. Environmental impacts on poultry
farms arise directly from energy use, housing, and
manure management. To enhance environmental
sustainability, it is crucial to measure and monitor
the level of environmental impacts overall.
Improving poultry housing and developing new
strategies for manure management have the
potential to further improve the environmental
sustainability of the poultry industry (Costantini et
al., 2021).
Maintaining optimum environmental conditions
needs proficient and stable poultry house
management at every stage of production (Flora et
al., 2022). Environmental factors, including
temperature,
humidity,
ventilation,
gas
concentration, and lighting, profoundly influence
poultry health and performance (ElZanaty, 2014;
Sarıca et al., 2018; Zhang et al., 2016).
Another vital aspect is litter management.
Contaminants, such as feed residues and faeces, can
lead to the proliferation of bacteria in the litter.
Accumulation of waste can result in increased
ammonia gas levels in the poultry house due to
microbial decomposition (Sakamoto et al., 2020).
High humidity in the litter also poses a significant
problem for flock health and welfare (Sakamoto et
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al., 2020). Therefore, the litter must be regularly
monitored and effectively managed throughout the
production cycle (Sakamoto et al., 2020).
Production
: Challenges in poultry production
encompass ensuring food safety while maintaining
low production costs. Expenses related to feed,
maintenance, and equipment constitute the
fundamental costs, but production losses also
significantly impact farming operations (Hafez and
Attia, 2020). Identifying low-yielding hens in egg
production and closely monitoring their egg-laying
behaviour can aid in cost reduction (Aral et al.,
2017; Dogan et al., 2018; Wu et al., 2022).
Free range systems in poultry farming are a
method of where hens are provided access to
outdoor areas for at least part of the day (Miao et
al., 2005; Petek and Cavusoglu, 2021). These
systems give hens to areas with nests, perches and
litter, allowing them greater mobility and
opportunities for natural behaviour (Hartcher and
Jones, 2017). However, it’s important to note that
floor egg problems can arise in these systems,
leading to reduced production (Oliveira et al.,
2019). Collecting eggs from the floor becomes a
daily task, which increases labour costs.
Additionally, eggs left on the floor can be broken or
eaten by birds. Moreover, if the eggs are not
collected promptly, they may mix with the litter
and manure, elevating the risk of contamination
and adversely affecting food quality and safety (Li
et al., 2020a; Chai, 2022).
Human-induced issues
: The general duties of
breeders in the poultry industry encompass daily
care of the animals, health, and welfare control, and
monitoring of the poultry house. Additionally,
breeders are responsible for the daily egg
collection and dispatch in laying hen breeding.
However, with the increase in herd size and the
adoption of different breeding systems, the
observation and management of the herd have
become more challenging (Vroegindeweij et al.,
2018). Manual observations are labour-intensive,
time-consuming, costly, and prone to subjective
information (Parajuli et al., 2020). Therefore, the
implementation
of
automatic
monitoring
equipment and effective use of technology is
imperative to achieve efficient monitoring and
informed decision-making (Buijs et al., 2018; Buijs
et al., 2020; Vroegindeweij et al., 2018).
Furthermore, breeders' increased activities within
the poultry house may cause stress in the animals
and lead to cross-contamination by carrying
disease factors between the birds. Such situations
pose risks to occupational health and safety (Ren et
al., 2020). The robots discussed in Section 3 offer
potential solutions to overcome human-induced
problems in poultry houses with their
functionalities.
Robots Used in Poultry Farming
The increasing interest in precision and smart
agriculture has prompted extensive research into
the application of AI and robotics in agricultural
production (Usher et al., 2017). Recent
advancements in hardware and software, including
robots, sensors, 5G networks, and cloud
infrastructures, have facilitated the abundant
evaluation of data in agriculture. These data are
invaluable for assessing and enhancing production
during the control and decision-making phases
(Park et al., 2022). Robotic systems that operate on
farms and assist breeders (Sahoo et al., 2022) are
expected to play a more prominent role in the
future, equipped with machine capabilities such as
perception, reasoning, learning, communication,
task planning, execution (Ren et al., 2020).
Robots find application in various agricultural
sectors, including planting, livestock, aquaculture,
and poultry farming (Sahoo et al., 2022). In the
context of poultry farming, both commercial and
experimental robots have been developed to
perform diverse tasks aimed at enhancing
production, reducing the workforce, safeguarding
animal health, and improving welfare, making
robots increasingly central in this area (Park et al.,
2022).
Poultry farming entails several tasks that need
constant monitoring, such as identifying sick and
deceased animals, monitoring environmental
conditions within poultry houses, cleaning,
disinfecting litter, and collecting floor eggs. These
tasks are laborious and repetitive (Abbas et al.,
2022). Robots have proven effective in information
detection and production management (Astill et al.,
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2020). Robots equipped with advanced sensory
and decision-making technologies have the
potential to efficiently execute designated tasks,
enhancing production efficiency (Ren et al., 2020).
Compared to humans, robots offer the promise of
superior accuracy, consistency, and efficiency in
monitoring birds and their environment (Mamun,
2019; Park et al., 2022). Human observations, in
fact, can be subjective, depending on the observer's
experience (Ren et al., 2020; Yang et al., 2020), and
might be too expensive to be performed constantly.
On the contrary, robots equipped with sensors
using artificial intelligence and machine learning
can continuously gather localized data as they
navigate through the poultry house. This sustained
real-time data collection can enable the timely
detection of diseases, food safety concerns, and
indoor environmental conditions through a robust
sensor network (Abbas et al., 2022; Park et al.,
2022).
Robots can contribute to increased biosecurity and
reduced human-animal interactions in poultry
houses, as they reduce the need for frequent
human intervention (Gittins et al., 2020). Daily
inspections are essential to ensure the proper
functioning of systems and the well-being of the
animals. Breeders must traverse the poultry house
multiple times a day to observe the animals and
monitor their behaviour and living conditions
(Abbas et al., 2022; Parajuli et al., 2020; Park et al.,
2022).
However,
human
breeders
may
inadvertently become disease vectors, transferring
pathogens and viruses between houses and cross-
infecting flocks, leading to the rapid spread of
diseases (Park et al., 2022). By replacing human
labour with robots, the potential for human-
induced issues is diminished, and biosecurity is
improved by reducing human activities in the
henhouse.
Environmental Monitoring
: To enhance poultry
management in both layer and broiler farming,
constant monitoring of the poultry house and
animals is essential. Environmental monitoring
provides valuable data such as farm air quality,
temperature, humidity, air velocity, and carbon
dioxide levels for poultry management and
assessment of animal health and welfare (Park et
al., 2022). Real-time data acquisition facilitates
informed
decision-making,
including
the
maintenance
of
favourable
environmental
conditions for optimal production and the early
detection of disease outbreaks. Furthermore, these
data contribute to improving operational
productivity (Astill et al., 2020; Kaur et al., 2021;
Olejnik et al., 2022; Wolfert et al., 2017). Therefore,
robots equipped with sensors, cameras, and other
systems can contribute to the development of the
poultry industry (Astill et al., 2020; Zhang et al.,
2016).
Scout (2023), (formerly known as ChickenBoy,
developed by Faromatics, Spain), is a robot that
works suspended from the ceiling, about half a
meter above the birds.
Fig. 1: Scout (2023), (formerly known as ChickenBoy, developed by Faromatics, Spain)
This autonomous robot is equipped with thermal
and light cameras, sensors for temperature,
humidity, air velocity, CO2, NH3, light, and sound,
as well as a laser pointer to stimulate the
movement of birds. As indicated in the product
specifications, this robot can control the
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distribution of birds, detect sick and dead birds,
and identify wet spots on the litter and drinkers
without direct contact. The robot enables early
diagnosis of intestinal diseases by monitoring bird
faces and provides images for the detection of leg
health. The breeders receive updates from the
robot via text message or emails.
Poultry Patrol (2019) is produced by a robotics
company that designs multi-tasking robots. Per the
robot's intended application, the robot, equipped
with autonomous and remote-control capabilities,
can monitor farms and animals using various types
of integrated cameras. It provides early warnings
to breeders by identifying sick and deceased birds
through remote monitoring and video recording
features.
Fig. 2: Poultry Patrol (2019)
Liu et al. (2016) designed a mobile robot equipped
with an intelligent poultry monitoring system. The
robot collects environmental parameters and
obstacle information related to poultry and
transmits this data to the host wirelessly.
Subsequently, the host performs data acquisition,
processing, display, storage, and remote control.
Octopus XO (2021), developed by Octopus
Biosafety, is a multi-task robot capable of collecting
various
environmental
data,
including
temperature, humidity, CO2, ammonia, sound, and
light intensity.
Fig. 3: Octopus XO (2021)
Disease control
: Pathogenic infections are among
the most critical challenges in poultry farming, as
they can spread rapidly within the poultry house.
Researchers have focused on developing robotic
systems to quickly identify sick animals and
remove dead birds from the herd (Li, 2016).
Equipping robots with sensors for early warning
systems allows the monitoring of disease and food
safety-related pathogens in birds (Abbas et al.,
2022; Park et al., 2022).
Nanny robots (Charoen Pokphand Group) are
designed to monitor the div temperature and
movements of animals in conventional 3-layer cage
systems using thermal cameras. The robot can
detect sick and dead chickens by identifying birds
with abnormal temperature values and inactivity
(Chicken Nannies, 2017). Li (2016) designed a
robot to identify sick and dead birds in cages. The
robot warns the animals by hitting the cage and
detects the movements of the birds using image
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processing methods. However, the manual
operation and hitting action may cause increased
stress in birds.
Fig. 4: Nanny robots
Liu et al. (2021) designed a robot with two modes
to remove dead chickens from the poultry house.
One mode allows for remote control, while the
other is autonomous, and the system can work
without human intervention. The robotic system
includes arms, a conveyor belt, a storage area, and
a sweep- in device. Dead chickens are identified
using the YOLO v4 algorithm, an object detection
network based on deep learning (Bochkovskiy et
al., 2020; Redmon et al., 2016). The system exhibits
high reliability, with accuracy, precision, and recall
rates of 97.5%, 95.24%, and 100%, respectively.
However, recognizing dead chickens poses a
challenge because the dead birds' shapes are
incomplete and look very similar to a healthy
chicken in a sitting or lying position. This similarity
can impact the accuracy of image classification. To
enhance precision and accuracy, the size of the
training dataset for the model should be increased
and identification errors should be reduced. Li et al.
(2022) developed a robot equipped with a camera
and two grippers mounted at the end of a robotic
arm, designed to remove dead chickens.
Fig. 5: Li et al. (2022) Robot
The robotic arm (Gen 3, Kinova Inc., Boisbriand, QC,
Canada), along with the camera and two grippers
(Robotiq 2F-85, Kinova Inc., Boisbriand, QC,
Canada) at the end, was securely mounted on a
table. The robot underwent testing to assess its
ability to grasp and lift dead chickens present on
the table under varying light intensities. The robot
arm has a maximum payload capacity of 2000 and
can move with 7 degrees of freedom, allowing for
versatile motion. The success rate of finding and
collecting dead chickens was evaluated at different
light intensities, resulting in rates of 53.3%, 80%,
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86.7%, 90%, and 90% at 10, 30, 60, 70, and 1000
light intensities, respectively. The robotic arm in
question has been specifically engineered for the
purpose of retrieving deceased chickens from a
stationary table. It is important to note that this
robotic arm has not yet undergone testing within
the dynamic environment of a live poultry house.
Furthermore, research findings reveal a
noteworthy observation: a decrease in light
intensity has been found to significantly impair the
performance of the deep learning model.
Specifically, this reduction in illumination
adversely affects the model's capacity for object
detection,
image
processing,
orientation
identification, and, ultimately, its ability to execute
the final pick-up performance (Li et al., 2022).
Poultry Patrol (2019) utilizes thermal imaging to
monitor the div temperatures of chickens as it
moves through the poultry house, enabling the
identification of sick and dead birds. Similarly, the
autonomous robot Scout (2023) employs an
infrared and visible light camera to detect deceased
chickens and diseases. Both systems monitor
temperature and bird movements to identify sick
and deceased animals in caged and cage-free
systems.
Collecting floor eggs
: The transition from cage
system to cage-free systems aim to improve the
welfare of laying hens (Ochs et al., 2019;
Vroegindeweij et al., 2016) by providing them
increased space for movement, perching,
dustbathing, and nesting. This transition allows
hens to spread their wings and express natural
behaviours, ultimately leading to a reduction in
confinement-related stress (Bhanja and Bhadauria,
2018; Hartcher and Jones, 2017). However, in cage-
free systems hens may lay eggs in areas outside the
nest, such as corners of the hen house and dim
environments (Li et al., 2022). While cage-free
systems provide hens with various areas such as
nests, perches, and litter (Hartcher and Jones,
2017), floor eggs are a common occurrence in these
systems and reduce production performance
(Oliveira et al., 2019). Automatic egg collection
robots have been developed to address this issue.
Unlike commercial robots, scientific research on
the use of robots in poultry farming has primarily
focused on addressing the difficulty of collecting
floor eggs. These robots can also reduce human-
induced problems mentioned in section 2.4 by
reducing the need for human labour in egg
collection. Vroegindeweij et al. (2014) developed
an autonomous robot, PoultryBot, for collecting
floor eggs in poultry houses.
Fig. 6: PoultryBot
The robot, equipped with a spiral spring on the
front for egg collection, successfully collected over
95% of the eggs (Vroegindeweij et al., 2014b). This
robot can drive autonomously for more than 3000
m in a commercial poultry house and collect 46%
of 300 eggs. A collection failure occurred in
approximately 37% of eggs (Vroegindeweij et al.,
2018). The researchers suggested that by
improving navigation, obstacle handling and
control algorithms, the robot could be used in
commercial poultry houses and dense animal
environments in the future (Vroegindeweij et al.,
2018).
Chang et al. (2020) designed a mobile egg
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collection robot using a computer vision-based
platform that can recognize white and brown eggs
in free-range farms.
Fig. 7: Mobile egg collection robot
The robot moves toward the eggs with visual
tracking, collects them, and stores them in its
chamber. In experimental tests, the robot collected
between 60% and 88% of the eggs on flat and
surrounded floors. Additionally, the robot could
collect 8 eggs in 10 minutes in a 25 m2 area. For the
robot to function efficiently, it relies on a flat
surface free of objects such as egg-shaped stones
within its operational area (Chang et al., 2020).
Therefore, performance enhancements are
necessary when deploying it in a free-range
system.
Joffe and Usher (2017) developed GohBot, an
autonomous egg-collecting robot that uses a
mechanical arm with a vacuum mirror to collect
eggs.
Fig. 8: GohBot
In tests, the success rate of egg collection was
91.6%. Li et al. (2021) developed an egg-collecting
robot consisting of a deep learning-based egg
detector, arm, gripper, and camera.
Fig. 9: Robotic arm
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Eggs detected by image processing algorithms are
collected using the robot arm and grippers. The
robot collected brown and white eggs with a
success rate of 92% to 94%.
Overall, egg collection robots developed for use in
cage-free systems face general challenges, such as
1) mobility within the poultry house, including
localization, navigation, path planning, and
obstacle avoidance, 2) detecting eggs, 3) collecting
eggs without breaking them, 4) storing eggs and
possibly classifying them according to weight and
shape.
Disinfection and litter management
: The floor of
the coop can become contaminated with bird
faeces and food residues, leading to air pollution
and the proliferation of pathogens. Regular
cleaning and disinfection of the house are
necessary to maintain animal health (Wu et al.,
2022). Robots can be effectively used for smart
production and appropriate disinfection in poultry
houses (Feng et al., 2021). Proper litter
management is essential for poultry farming, and
regular litter scraping can help aerate the litter,
preventing fermentation and reducing litter
moisture (Tibot, 2021). Robots designed for litter
scraping can address litter management challenges
and support animal health.
Feng et al. (2021) designed an anti-epidemic (Feng
et al., 2021) and disinfection spray (Feng and
Wang, 2020) robot for use in poultry houses and
farms. Comprising a robot, transport vehicle,
sensors, spraying unit, and controller, it can work
autonomously and with remote control.
Fig. 9: Disinfection Robot
The researchers proposed the "Magnet-RFID" path
detection navigation method for autonomous
movement, which involves the manual installation
of magnets and RFID (Radio Frequency
Identification) electronic tags in the work area. The
robot successfully ensured sufficient drug
concentration in various parts of the cages to kill
pathogenic microorganisms (Feng et al., 2021). As
indicated in the product specifications, Octopus XO
(2021), a multi-tasking robot, can autonomously
move within the poultry house to scrape the litter
and prevent the formation of scabs. It also reduces
ammonia formation by providing better litter
drying and performs litter cleaning by spraying a
disinfectant solution. Spoutnic-NAV, another robot
developed by Tibot, aerates the litter through the
forks mounted on the back while moving in the
poultry house (Tibot, 2021).
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Fig. 10: Spoutnic-NAV
Enhancing bird activity
: Birds need physical
activity to maintain their health and well-being.
Inactive or sedentary behaviour for extended
periods can lead to health issues in birds (Abbas et
al., 2022). With the development of production
systems characterized by rapid growth rates in
broilers, fast-growing strains are used in
commercial breeding (Zuidhof et al., 2014). It has
been reported that faster-growing breeds have
higher inactivity, behavioural traits are affected by
the growth rate, and fast-growing breeds sit more,
feed more, and walk less than slow-growing breeds
(Dawson et al., 2021; Hartcher and Lum, 2020). As
higher activity can reduce litter contact, more
active animals have been evaluated to have better
feather cleanliness, lower hock burn levels and
better leg health (Casey-Trott et al., 2017; Dixon,
2020; Hartcher and Lum, 2020). Robots have been
shown to be effective in encouraging movement in
broilers, leading to improved bone quality in
animals (Hartcher and Jones, 2017; Janczak and
Riber, 2015).
The two main approaches used in free-range
poultry farms to encourage animal movement are
mobile robots and laser pointers. Mobile ground
robots that move within the poultry house trigger
the animals around them to move as well (Li et al.,
2022; Tibot, 2021; T-Moov, 2022).
Fig. 11: T-Moov
Alternatively, robots with laser pointers project
laser lights onto the floor, encouraging the birds to
move (Scout, 2023). Tibot Technologies claim that
their commercial autonomous mobile robots, T-
Moov and Spoutnic NAV, increase bird activity in
the poultry house and mitigate the issue of floor
eggs in cage-free systems. Additionally, increased
bird activity resulted in higher feed consumption
and a natural weight gain of 300 grams per animal.
Moreover, active birds required fewer antibiotics
to achieve weight gain naturally (Ren et al., 2020;
Tibot, 2021; T-Moov, 2022).
The robot Octopus XO serves the dual purpose of
litter cleaning while stimulating bird activity with
laser pointers (Octopus XO, 2021). Similarly, the
robot Scout (2023) has asserted its capability to
stimulate animal activity through the utilization of
laser pointers. Li et al. (2022) reported that a
ground robot designed to reduce floor eggs also
effectively encouraged bird movement. Another
study by Yang et al. (2020) found that robots
significantly increased the activity of broilers.
Robots use in poultry farming: Challenges and
Solutions
Overall, robots for poultry farming are still limited
in functionality and adaptability, since most robots
are designed to perform a single, specific task (Ren
et al., 2020; Wu et al., 2022). Hence, research
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should expand multi-tasking abilities, via sensor
integration and advanced technology, including AI
(Alatise and Hancke, 2020). For instance, in the
context of collecting floor eggs and managing dead
birds, robots face several challenges. These include
difficulties in accessing different locations within
the poultry house, issues with target identification
and capture due to factors such as poultry house
infrastructure, bird movements, changing light
intensities, and secluded areas. Moreover, robots
designed to collect floor eggs encounter challenges
in collecting eggs without breakage, as well as
sorting and storing them (Chang et al., 2020; Li et
al., 2022b; Vroegindeweij et al., 2018). To address
these challenges, robots should be designed to
operate effectively across various environmental
conditions and production systems. To this aim,
reliability of visual and tactile perception,
combined with flexibility and safety of the
movements, are particularly important. The
development of algorithms related to object
detection, localisation, navigation, path planning,
and control is essential. Some robots can be
operated manually and by remote control (Li,
2016; Yang et al., 2020), however, there is a need
for autonomous work, reducing the need for
constant manual or remote control. Visuo-tactile
perception is crucial for autonomous robotic
systems, especially if they have to grasp and
manipulate objects (Navarro-Guerrero et al.,
2023).
An important issue is the difficulty in avoiding
obstacles while navigating within the poultry
house (Dennis et al., 2020; Vroegindeweij et al.,
2018). During the movement of robots, the
unpredictable actions of the surrounding chickens
can impact the detection of static obstacles.
Simultaneously, the robots need to make necessary
evasive maneuvers with respect to the moving
chickens. These requirements impose a high
demand on the robot's environmental perception
capability and real-time path planning when
confronting mobility-related challenges (see
Section 2) including those associated with
production and human-induced factors. It will be
crucial to develop obstacle awareness systems to
improve navigation and guarantee animal welfare.
Most studies on robotic applications in poultry
farming have primarily focused on free-range
systems. However, robots that come into direct
contact with animals pose a risk of harming
animals and, as a result, may operate at a slower
pace (Abbas et al., 2022; Wu et al., 2022). To
mitigate these risks and challenges, robots should
be designed with the ability to avoid and regulate
contact. A current solution is non-contact systems,
such as those involving robotic arms mounted on
the ceiling of the farm. However, these systems can
hardly be implemented in existing farms and would
require restructuring or building of dedicated
facilities,
complicating
the
logistics
of
implementation. Hardware solutions to reduce the
risks of robot harming animals include protective
equipment, such as robots built with soft materials.
In some situations, robot-animal contact is
necessary. In cases where robots are deployed for
the identification of sick birds, an additional
capability for capturing and isolating animals has
been shown to be viable when employed within an
operational poultry farm in conjunction with the
detection system (Liu et al., 2021). For enhanced
welfare and biosecurity, robots should also
incorporate an early warning system to promptly
intervene in cases involving sick birds.
Poultry farms differ in size and organisation (Ren
et al., 2020). However, most robotic studies are
conducted
in
controlled
experimental
environments or within small-scale poultry houses
(Vroegindeweij et al., 2018; Wu et al., 2022).
Further tests and development are needed for
large-capacity poultry houses, including tests on
the integration of multiple robots to working
together efficiently, in accordance with the size of
the poultry house.
Effective and safe robot-animal interactions
require knowledge of the species-specific needs in
terms of social interactions. Research has just
started to address these areas, with few studies
that identify social learning mechanisms that can
improve welfare and health in interactions with
robots (Gribovskiy et al., 2018; Mostafavi et al.,
2010). Further research is needed to understand
how robots can be best integrated in commercial
farms, from the point of view of hardware design
and functionality.
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Robot-animal interactions present opportunities
and challenges. Ground-based robotic systems
offer a promising avenue for enhancing animal
mobility, with potential benefits for chicken
welfare. Such benefits include a reduction in litter
contact (Dixon, 2020; Hartcher and Lum, 2020), an
improvement in bone quality (Hartcher and Jones,
2017; Janczak and Riber, 2015), as well as
enhancement in foot health and feather condition
(Yang et al., 2020).
At the same time, robots increase birds
’ energy
consumption, with effects that have just started to
be investigated. It has been suggested that this
activity might o reduce egg nutrient accumulation
in laying hens and decrease egg weight (Li et al.,
2022b). Future research should target various
parameters such as food consumption, egg weight
and food conversion rate to assess the effect of
robot use on overall yield in commercial poultry
farming.
Potential stress arising from interactions between
robots and animals, and whether robots pose lower
or higher challenges to animals, are object of
research. Ground robots, as they move around
poultry houses, exhibit the potential to reduce the
incidence of startling behaviour compared to
human breeders, while simultaneously mitigating
the risk of disease transmission within the poultry
house (Park et al., 2022). Differences of responses
to robots within the life course have not been
investigated enough (Parajuli et al., 2018).
Remarkably, research has revealed that chickens
exhibit a propensity to form attachments to non-
naturalistic agents, such as robots (Gribovski et al.,
2018; Slonina et al., 2021). Furthermore, early
exposure to robots can effectively mitigate fear
reactions towards these artificial agents (Dennis et
al., 2020).
The use of robots can be costly, especially for small-
scale coops operations (Abbas et al., 2022; Mamun,
2019). It is crucial to conduct economic analyses to
assess the viability of using robots in poultry
houses. Such analyses should consider their
potential effects on human labour, animal health,
and production output to make informed decisions
about investment.
Creating robots tailored for various functions in
poultry farming demands a collaborative approach
that delves into multiple domains, such as
mechanical engineering, software development,
data analytics, genetic animal breeding, animal
behaviour, and animal welfare (Zhou et al., 2022).
This diverse integration of specialized knowledge
is essential in designing robotic solutions that
precisely address the intricate demands of poultry
farming,
ensuring
optimal
performance,
operational efficiency and animal well-being.
CONCLUSION
The exploration of robotic technology for poultry
farming has enormous promise awaiting
realization. The current research landscape,
though limited, indicates the potential for robots to
innovate poultry farming, reducing labour
dependency
and
significantly
enhancing
management efficiency by aiding in animal and
environmental monitoring. However, this potential
has only just begun to be tapped. Further research
is needed to fully harness the benefits of robotics in
supporting efficient production and promoting
animal welfare.
As the poultry industry delves deeper into the
integration of robotic technology, the focus must
emphasize the critical aspect of robot-animal
interactions. Achieving effective solutions calls for
the fusion of engineering innovation with a
comprehensive understanding of animal needs and
behaviour, as underscored by recent research
work on imprinting and predispositions in poultry
chicks (Rosa-Salva et al., 2021; Versace et al., 2018)
and in adult chickens (Dennis et al., 2020; Nicol,
2023). One of the challenges ahead involves the
need for increased data sharing and open-source
development. Addressing these challenges and
fostering collaboration is crucial for a
comprehensive understanding of animal welfare.
Overall, the integration of robotic technology and
innovation with a deeper understanding of animal
needs and societal demands presents a
transformative opportunity for enhancing both
productivity and welfare in poultry farming. To
fully realise this potential, increased research,
collaboration, and attention to the animal welfare
within robotic applications are essential.
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