Journal of Advances in Artificial Life Robotics
Vol. 1(4); March (2021), pp. 168–174
ON LINE ISSN 2435-8061; ISSN-L 2435-8061
https://alife-robotics.org/jallr.html

SUGISAKAMASANORI

Research Article

Cradle DesignIntelligence

andImplementation

Based

on

Artificial

Ting Zhao, Qing He, Zhuofan Xu, Zhou Yang, Zhenjiang Chen, Shuo Jiang
Tianjin University of Science and Technology, Tianjin, 300222, China

ARTICLE INFO
Article History
Received 25 October 2019
Accepted 07 September 2020
Keywords
Bionic cradle
Infant crying
ROS
Natural language interaction
Autonomous navigation

ABSTRACT

In order to reduce the burden of child care and better child care.A cradle with artificial intelligence
technology is designed for families to raise child . The data of baby shaking are collected andanalyzed by the Micro Control Unit, so that the cradle bed can bionic cradle shaking. The SVM
database training of infant crying can realize the recognition of infant crying and determine thespecific meaning of crying, such as hunger, excretion, pain and other factors, and timely informparents; Based on ROS robot operating system and iflytek platform, it can carry out natural
language interaction and autonomous navigation. Parents can call the baby cradle and let it reachthe designated position automatically to achieve autonomous obstacle avoidance and path
planning without manual interference. At the same time, the camera can view the baby's status
and transmit the real-time picture to the mobile phone APP.

© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd.
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

1. Introduction

they have to work hard, leaving little energy left for theirchildren every day. Some parents can not get a good rest
for a long time because they need to take care of theirbabies at night, and even seriously affect their health andnormal work. In order to reduce the pressure on young
parents to coax their babies, automatic baby cradles haveemerged.

Since entering the 21st century, the development of robots
has become faster and faster. With the development ofscience and technology, the integration degree of robot ishigher and smaller. The diversified functions of service
robots are gradually recognized by the market. According
to China's industrial information network, the sales
volume of service robots in 2016 was 6.8 million, an
increase of 25.93% compared with 2015. From 2011 to2014, the global average compound growth rate of home
service robots is about 22%, and the sales volume isexpected to increase to 31 million in 2019. Service robots
will affect all aspects of human production and life.

In the early days, the baby cradle simply replaced theparents' hands. The simple mechanical transmission
structure could only output at a fixed frequency, so thebaby could not feel the feeling of "parents". In the new
century, the electric baby carriage has only added
recording and playing functions, so parents still have todevote a lot of energy to taking care of their children.

The pace of contemporary society is speeding up, and thework pressure is increasing. For young people who areabout to become parents or have already become parents,
the pressure is even more significant. On the one hand,
they have no experience as a parent, and on the other hand,

In order to solve the pain point of parenting, we havecarefully designed the intelligent cradle bed. It can imitate
the parents' cradle frequency, understand the baby's crying,such as whether it is hungry, report the child's physicalCorresponding author’s E-mail: heqing@tust.edu.cn, URL: www.tust.edu.cn

168crying, and intelligently judge crying caused by hunger,
excretion or pain, so as to timely inform parents and informtheir children of the situation.Voice interaction can realize
parents’ call for bassinet autonomous navigation to parents.

condition to the parents, such as whether it has a fever, etc.
it can also move autonomously to the place where theparents want it to go. It is the intelligent nursing sister-inlaw who liberates parents.
In today's information age, people are busy in various
activities and affairs, such as work, social interaction andso on [1]. According to the statistics of the United Nations,
140 million newborns were born in the world in 2018, with
15.23 million in China alone. With the opening of the twochild policy, the number of newborns is increasing year by
year [2]. A large group of novice parents urgently need amore labor-saving care service robot [3]. In order to solve
the problem of parenting, we have developed an intelligent
cradle, which can imitate the cradle frequency of parents,
understand the crying of babies, and move autonomously,
so that novice parents are more relaxed.

3. The hardware structure design
The core platform of the device is the robot operating
system (ROS). Its distributed network uses thecommunication mode of TCP / IP to realize the point-topoint loose coupling connection between modules. The
hardware consists of raspberry pai, camera, lidar,
ultrasonic ranging sensor, motor, omni-directional wheel,encoder, drive board and beidou module. The encoder isinstalled on the cradle motor to calculate the rotation angleof the cradle and fix the rotation angle from the mechanicalstructure and the upper limit of the software program; thedrive board controls the movement of the baby carriage
chassis, the chassis adopts three omni-directional wheels,
which can realize the omni-directional movement abilityof the baby carriage; the microphone recognizes the baby
crying for data collection and processing, and uses
iFLYTEK platform for natural language Interaction; thecamera is used to observe the situation in the stroller andtransmit the real-time picture to the mobile app; theultrasonic ranging sensor is installed around the stroller
chassis to avoid obstacles; the lidar and Beidou module areused to collect the surrounding environment information at
the same time, which can collect information moreaccurately, understand the structure of the house, andtransmit the collected data to raspberry pie for slammapping, so as to realize indoor autonomous navigation.

2. System overview
This equipment is a cradle bed combining artificial
intelligence technology. The cradle bed can realize many
functions such as automatic follow, intelligent cradle,
natural language interaction, early childhood education,
cry recognition, etc. Cradle bed integrates speech
recognition and processing and big data processing
technology. By installing ROS platform in raspberry pi, its
distributed framework can build voice interaction module,
bottom motion module, Bluetooth communication module,etc. Three special functions can be realized: first, imitating
the swing frequency when human coax the baby,
automatically rocking the cradle with different degrees ofbionic frequency, imitating grandma gently rocking,imitating mom to coax the baby to sleep rocking, imitating
dad to play rocking, and at the same time, timing the cradle
timeSecond, autonomous navigation. Based on slamtechnology and Beidou navigation, the environment layout
map can be quickly constructed when the bassinet moves
in an unfamiliar environment, which can provide accurate
positioning and navigation reference for the autonomous
movement of the bassinet, as well as the reference forhuman-computer interaction. With real-time positioning,
intelligent obstacle avoidance, path planning and otherfunctions, the device can automatically move to any indoor
accessible place, realize fixed-point movement, fullautonomy, without manual interference. Thirdly, it isequipped with voice interaction system, based on
iFLYTEK platform, and collects big data of baby crying.
It can communicate with parents by voice, recognize baby

3.1. Chassis motion control structure
The bassinet chassis is made of aluminum alloy. Because
the bassinet needs to have safe omni-directional movement
ability in the room, the omni wheel ql-10 (Omni wheels isa wheel that can move in many different directions) is
selected as its moving tool. It includes a wheel hub and aplurality of driven wheels. Each driven wheel is embeddedwith two rolling bearings. Compared with the mcnamm
wheel, the omni-directional wheel has faster speed, more
flexible movement mode and more stable movement
system. When three omni-directional wheels are used at
the same time, the translation in any direction can berealized, and any complicated arc motion can be
performed. The driving mode is three-wheel independent
driving, three hollow cup DC servo motors control three169

The motor is connected by the rocker. The motor rotates todrive the rocker to swing back and forth. The rotation angle
and speed of the motor are calculated by the encoder. The
control board yf00702ea controls the maximum rotation
angle of the motor to prevent the shaking from being too
intense. At the same time, in the mechanical structure, theshaking limit position is designed to prevent the parents
from throwing the baby out by mistake. The cradle motorand encoder are shown in Fig.3 and the control board
YF00702EA is shown in Fig.4. Servo driver workflow isshown in Fig.5.

omni-directional wheels respectively and use imdr4e servo
driver to drive the motor via CAN bus and RS232
communication interface. The maximum moving speed ofbassinet is 0.65m/s, the maximum rotation speed is 200 °/ s, and the minimum turning radius is 0m. The chassis isslightly lower, so it is suitable for indoor and flat road
operation. When working indoors, for the safety of thebaby, anti-collision strips are installed around and aroundthe chassis to prevent the baby from being injured due tothe movement of the baby carriage. The chassis structureis shown in Fig 1.

Fig.3. Motor and encoder
Fig.1. Chassis structure

3.2. Cradle mechanical structure
The bassinet structure is arranged on the bassinet chassis,
which is composed of four brackets, an electric motor, arocker and a bassinet. Two brackets are set up on bothsides to fix on the chassis, one side of which is fixed to
install the motor, the motor is connected with the rocker,
the other side is directly connected with the rocker, and thetwo rocker are connected with the cradle. Through the
motor to give the rocker force, through the rocker swing todrive the cradle swing. The mechanical structure of cradleis shown in Fig.2.

Fig.4. Control board YF00702

Fig.2. Cradle rocker structure170

3.4. Laser radar
Lidar systems are often based on pulsed laser diodes andsilicon avalanche photodiode (APD) arrays, with
exploiting 905nm wavelength light [5]. It is used to collectthe information of the surrounding environment, transmit
the collected data to raspberry pi, and use it for SLAM
mapping to realize the indoor autonomous navigation, as
shown in Fig.7.

Fig.7. Experimental construction

4. System circuit module design
4.1. Research and analysis of CAN bus
Fig.5. Servo driver workflow

The Controller Area Network (CAN bus) is a bus based on
differential signaling originally developed for automotive
industry [6]. CAN bus topology and physical layer, canbus bit value representation is shown in Fig.8.

3.3. Ultrasonic obstacle avoidance sensor
The model of ultrasonic obstacle avoidance sensor used inthis bassinet is ULB-1 ultrasonic distance sensor, which
has the characteristics of high resolution, high precisionand low consumption. Not only in the design, but also in
the interference noise processing, with anti noiseinterference ability. And for the different size of the target,
and the change of the supply voltage, do the sensitivity
compensation. In addition, it also has standard
internal
temperature compensation, which makes the measured
distance data more accurate [4]. ULB-1 ultrasonic ranging
sensor is shown in Fig.6.

Fig.8. CAN bus bit value characterization

Compared with other network protocols, CAN has thefollowing two outstanding advantages:● Good reliability. The data transmission adopts shortframe mode, and the transmission medium is double
insulated wire. It can effectively shield all kinds ofexternal electromagnetic interference. At the sametime, can defines a variety of fault diagnosis
mechanisms, which makes it has high reliability, andis very suitable for use in controller subnet [7].
● good expansibility. CAN adopts multi main mode
communication, and the identifier is defined in theFig.6. ULB-1 Ultrasonic ranging sensor

171frame structure. The access of controller in the
network does not require any change of software or
hardware of all controller application layers.
4.2. Crying recognition

In the project of "donating crying" shared on GitHub, 450
clear baby crying data were obtained by filtering the data
recorded and uploaded by users' mobile phones. The
duration of the data was about 5S. The data was converted
to CAF or 3gp, and the unified bit format was 128kbps.
The whole data was converted to WAV format, and thesampling rate was 8kHz. Feature extraction method ofbaby crying: when the baby cries, the detection device(microphone) will receive the signal, and then throughfiltering processing, and then through the basic acoustic
features to extract the feature data [8]. Baby crying can bedivided into several crying units, which have different
acoustic characteristics. The flow chart of cry recognition
system is shown in Fig 9.

Fig.10. Two microphone array for corpus sample analysis

The crying type expiratory crying unit calculates thefundamental frequency (F0) and the first (F1), second (F2)and third (F3) formants of the crying signal frame by frame
The fundamental frequency corresponds to the frequencyof the glottal pulse excitation signal, and the resonancepeak corresponds to the resonance frequency of thechannel.
The device uses SVM cry recognition model, uses
tensorflow in-depth learning keras tool kit to realize SVM
model, Support Vector Machine (SVM) is a supervisedmachine learning algorithm. Firstly, preprocessing andfeature extraction are carried out, including removing
silent segment, adding window, framing and amplitude
normalization. The feature vector extracted by SVM
experiment is the statistical average feature of all frames
in each corpus.
For the identification of this product, we use the kernel
function with the highest recognition rate in the laboratory
process, which is Gaussian kernel function, as the SVM
baseline model.
5. Testing and conclusion
5.1. Test plan
The test scheme of omni-directional wheel is as follows:● Write the control program of the omni-directional
wheel, and then place it close to the longer wall andmove it freely, so that it can directly observe thechange of the gap between the intelligent bed and thewall, and record the error.
● Place the intelligent bed on the flat and easy to observe
ground, determine its geometric center and mark it on
the ground, make it rotate around the center point,
observe the bed offset after a period of time, andrecord.
● Place the intelligent bed at the right angle bend, makesure the ground is flat and smooth, make it pass theright angle bend continuously, observe the friction
and deviation, and record.
The test scheme of the shaker is as follows:

Fig.9. Flow chart of cry recognition system

As shown in Fig.10, there are three expiratory crying units(segments 1, 3 and 5) with longer duration and lower
fundamental frequency, and two inspiratory crying units(segments 2 and 4) with shorter duration, dullness andhigher fundamental frequency The duration of inspiratory
crying unit is short, and sometimes it is pure sound,sometimes it is dullness, and its acoustic characteristics are
not stable, so breath crying unit is used for analysis.

172

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● Set the intelligent bed to a fixed gear, record theincluded angle and time, calculate the shaking
frequency, record a long time, and calculate the error.
● Put the intelligent bed in different gears, and compare
the changes of amplitude and frequency.
● Place the intelligent cradle on the irregular ground andobserve whether it is stable
The scheme of ultrasonic obstacle avoidance test is asfollows:● Place the intelligent bed in the open and flat space, set
obstacles of the same specification in the surrounding
fixed area, so that the bed can only move towards the
direction of the obstacles, return to the original place
after the successful detection of the obstacle
avoidance, and then move to other directions to judge
the success probability and efficiency of the obstacle
avoidance.
● Change the shape of obstacles, and then conduct
obstacle avoidance test. Record data and analyze.
Bluetooth Test: transfer data of different types and sizes
into Bluetooth at one time, and judge whether Bluetoothis in fault by many experiments. Is the data collected byBluetooth fully fed back to raspberry pie to make thecradle work normally
The cry recognition test scheme is as follows:● Put the cry data collected from the same infant withdifferent purposes into the in-depth learning module,
and compare the results of learning prediction with theactual situation to get the probability of success.
● uPut the cry of different infants into the deep learning
module to detect the success rate of deep learning.

Authors Introduction
Miss. Ting Zhao

She is now an undergraduate student
at Tianjin University of Science &Technology. Her research field is
controlscienceandcontrolengineering, and intelligent control is
her research direction.

5.2. Test results
After repeated tests, the crib can meet the needs of users
for safety and intelligence, achieve the real sense of"people-oriented" [9], and protect the baby from harm in
the daily life environment, with stable hardware andsoftware. Omnidirectional wheel works safely andnormally, avoiding obstacles accurately and timely.
Bluetooth receives all kinds of data and works normally. It
also has a certain recognition success rate for children's
crying, which can help parents understand their children's
physiological needs.

Dr. Qing He

References
1. Aiyan Wu, Xuewei Cui. Research progress of home robots[J]. Journal of Tangshan University, 2009, 22，3，pp. 69P71
2. Binkun Liu,,Haitao Liu,Design of Intelligent Security
stroller for data Communication based on STM32,Scienceand Technology & Innovation, 2018, 16, pp. 62-P63.

173

He is a lecturer in Tianjin Universityof Science & Technology. He
received a doctor's degree in control
science and engineering from Schoolof Information, Zhejiang University,
in 2007. His research field is Nondestructive and intelligent detection
technology.

Mr. Zhuofan Xu

Mr. Zhou Yang

He is an undergraduate of Tianjin
University of science and technology.
After a period of study, he has
participated in some competitions andwon prizes

He is a second-year master candidate
in Tianjin University of Science andTechnology, majoring in instrument
science and technology. His research
firld is intelligent robot

Mr. Zhenjiang Chen
He is a graduate student majoring incontrol theory and control engineeringof Tianjin University of science andtechnology. His research direction isknowledge

Mr. Shuo Jiang

He is now an undergraduate in
Tianjin University of science andtechnology. His research direction is
automatic control theory.

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