ENGINEER - Vol. LIII, No. 01, pp. [55-61], 2020
© The Institution of Engineers, Sri Lanka
DOI: http://doi.org/10.4038/engineer.v53i1.7399
Design of a Tele-operable Soft Actuator
P.D.S.H. Gunawardane, R.E.A. Pallewela and Nimali T. Medagedara
Abstract:
Communication delay between robotic control systems and the robotic actuator is a
major issue since the soft robotic motion requires controls to be precise and have quick responses. This
is also essential for real time control of robots where the user should be able to send and receive signals
with minimum delay to emulate a real time control. Specifically, in soft robotics , the communication
delay could become a bigger issue due to the fact that soft robots require mode of pressure exerted into
the actuator to make any kind of motion. A delay in such instances could cause the whole system to
malfunction and even could cause the actuator to explode in the case of rapid and subtle changes in
internally applied pressure. In this research, available IoT (Internet of Things) related systems and
models have been studied and suitable IoT system was designed. The main focus of this research was
to study the communication delay in IoT embedded hand gesture controlled soft robot finger (actuator).
Two separate data processing units have been introduced in the master side and in the slave side to
rapid capturing and sending data. By using this approach , processing delay is expected to be
minimized. Transmission delay, propagation delay and queuing delay are found to be handled through
external factors. These factors could be changed by using various kinds of servers and service providers .
Soft elastomer actuator was designed and developed using standard rapid prototyping and soft
lithography techniques generally used in soft robotics. Testing, data collecting and analyzing the
system are carried out at various locations in Sri lanka and finally the Round Trip Delay Time (RTD) for
each case was compared.
Keywords:
IoT, Hand Gesture, RTD Delay Time, Soft Robot, Soft Actuator, Data Glove,
Finite Element Method
1.
Introduction
Soft Robotics is a sub field of robotics dealing
with non-stiff robots constructed with soft and
deformable material like silicon and rubber. It
consists of low cost simple components and it can
achieve complex motions. It allows for increased
flexibility and adaptability to accomplish tasks,
as well as provides improved safety when
working around humans. These characteristics
allow for its potential use in the fields of medicine
and manufacturing.
IoT facilitates the way individuals communicate
with nature and surroundings, and expands our
social relationships with other people and IoT is
Eng. P.D.S.H. Gunawardane, AMIE(SL), MIEEE,
B.Tech.Eng.(Hons) (OUSL), M.A.Sc. (UBC), PhD (Reading)
(UBC), Graduate Research Student in Department of
Mechanical Engineering, The University of British Columbia,
Vancouver, Canada.
Email:hiroshan@mail.ubc.ca
objects.
https://orcid.org/0000-0001-9195-6048
Eng. R.E.A. Pallewela, AMIE(SL), B.Tech.Eng. (OUSL),
Department of Mechanical Engineering, The Open University
of Sri Lanka.
Email:eashanmax@gmail.com
Internet of things (IoT) [1] is a system of
interrelated computing devices, mechanical and
digital machines, objects or people, provided
with unique identifiers and the ability to transfer
data over a network without requiring human to
human or human to computer interaction.
Figure 1 shows the interconnected commonly
used sensors and devices. IoT plays a major role
in all aspects in the world. It covers various fields,
including medical industry, automobile industry,
mechanical devices, sports and homes etc.
Eng. (Mrs) T.M.D.N.T. Medagedara, C.Eng., MIE(SL),
MIEEE, B.Sc. Eng.(Hons) (Peradeniya), MPhil. (SHU), Senior
Lecturer in Department of Mechanical Engineering, The Open
University of Sri Lanka.
Email:tmmed@ou.ac.lk
https://orcid.org/0000-0002-7210-0874
This article is published under the Creative Commons CC-BY-ND License (http://creativecommons.org/licenses/by-nd/4.0/).
This license permits use, distribution and reproduction, commercial and non-commercial, provided that the original work is
properly cited and is not changed in anyway.
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Table 1 - IoT layers and descriptions
Layer
Description
(1)
Contains objects such as sensors,
electronic robots that either collect
Hardware
data or are manipulated.
(2)
Network
Figure 1 - Inter connected commonly used
sensors and devices [2]
(3)
Internet
another revolutionary innovation that has
provided immense benefits and influenced
developments in how communication should be
carried out. IoT is a platform that permits
objects, including humans, to interact with each
other over the internet so that they would be
controlled, manipulated or simply share
information [3]. A typical IoT system consists of
5 layers: (1) hardware/robotic things layer, (2)
network layer, (3) internet layer, (4)
infrastructure layer, and (5) application layer.
Their descriptions are given in Table 1 [4]. This
architecture is highly helpful for robotic
manipulation.
(4)
Infrastru
cture
This layer is used to send and
receive packet data, messages &
TCP using protocols such as
MQTT, IPv6, DDS, AMQP, LLAP
&CoAP.
This layer is the operating
system/platform for the IoT
system which would include
cloud based and standard OS.
Examples are Robotic Operatin g
System (ROS) Robot Service
Network Protocol (RSNP) &RT
(Robot Technology) middleware.
(5)
This is the end user GUI system
that is used to manipulate the
Application
robotic system.
Developing applications for IoT could be a
challenging task due to (i) high complexity of
distributed computing, (ii) lack of general
guidelines or frameworks that handle low level
communication and simplify high level
implementation, (iii) multiple programmin g
languages, and (iv) various communication
protocols
[5].
IoT
characterizes
the
interconnection of different devices with
universal accessibility and built-in intelligence.
IoT has already modified the way we interact
with devices and provided us with novel
networking and socializing capabilities through
intermediary devices [6]. Several research
papers have compared the operating systems by
their architecture, structure, operation and
resource management but these comparisons
are restricted to a specific domain [7,8,9].
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Network
connection
allows
connection between devices using
modes such as long range 4G, 3G,
short range Wifi, Bluetooth, Near
Field Communication (NFC) and
medium long-range Microwave
Access (WiMAX) and zigbee.
To enable such interactions, several competitive
IoT application-layer communication protocols
(e.g., extensible Messaging and Presence
Protocol (XMPP) [10,11], HTTP REST [12-14],
MQTT [15,16], and CoAP [17]) have been
developed to satisfy the properties of
constrained ecosystems such as IoT. Each
protocol is designed for a particular set of
application requirements and aspects of IoT
communications, and these communication
protocols blur the line between messaging
mechanisms and semantic-based computation
[18].
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2
Methodology
control an output solenoid as shown in Figure 2,
which used air pressure to bend the soft robotic
actuator [22]. The server data was executed
according to the program in actuator control
board. Solenoid valve was used to control the
actuator. A well-positioned camera, close to the
soft robotic actuator, provided the feedback to
the person who wears the data glove so as to
adjust the motion accordingly (Figure 4).
2.1 Experimental Detection of Round Trip
Delay Time (RTD)
This research mainly focuses on the
development of a communication platform for a
soft robotic finger which is controlled through a
gesture controlled data glove [18], to study the
reduction in the communication delays between
two nodes, and suggest improvements for rapid
response of the system. Current IoT system for
soft robotics or solid actuator mainly faces data
losses during data packet transferring in the
communication system. Data loss during
transmission between receiver and transmitter
can occur due to interconnected breakdowns.
Communication delays occur as a result of data
losses in between two nodes. A designed system
isneeded to be capable of controlling and
monitoring from a long distance through the
internet. The results of internet-enabled gesture
controlled soft robot actuator provide a new
level of flexibility, performance and cost
advantages. Prevailing soft robot control
systems are limited to local area networks or
wire connected distance. On the performance of
this developed system it is possible to
communicate with actuator control station
anywhere in the world (Figure 2).
Figure 3 - Fabric based data glove
Data glove (Figure 3) was designed mainly for
extracting parameters to detect the angle of
bending and force on the ball. This unit consists
of two voltage dividers and an analog to digital
conversion unit.
Finger Gesture motion via 402km
ahead
Solenoid valve
Soft actuator
Soft Actuator
Figure 4 - Experimental setup for DG and soft
actuator
Ball
Soft actuator control
unit
MQTT Protocol (Figure 5) was used for the
research as the communication platform as
MQTT
has ability to achieve better
characteristics as a protocol to data
transmission [17,18].
Figure 2 - Soft Finger control unit
The system uses a fabric based data glove as the
input for the system (Figure 3). The data glove
gives orientation data (index finger gesture
angles) and force data which would then be
processed using a Raspberry Pi 3, which in turn
signals the output device via a communication
platform which can be used as a global
communication system. This data was used to
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2.3 Finite Element Modelling and Analysis
The behavior of the soft actuator was studied by
Finite Element Analysis (FEA). Standard Abacus
software was used to model the actuator and
8873 Tetrahedral Quadric Quadratic elements
with four nodes were used (Figure 6) for the
finite element analysis. Tetrahedral Quadratic
elements are formulated in three-dimensional
space with three degrees of freedom per node.
These are the translational degrees of freedom in
the X, Y and Z directions.
Figure 5 – MQTT broker diagram
The finite element model was used to find the
required pressure for bending and study the
behavior of the soft actuator, and also validate
the physical experimental data. Behavior of the
soft actuator was tested for the exact diameter
used in the experiment (Figure 6).
The algorithm measured the Round Trip Delay
Time (RTD) of the communication endpoints.
RTD is the length of time taken to send signal
and the length of time taken for an
acknowledgment of the signal received. Delays
between two network nodes are often
asymmetric, and also the forward and revers e
delays are not equal. Half the RTD value is the
average of the forward and reverse delays, and
therefore may be used sometimes as an
approximation to the one-way delay (OWD).
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐷𝐷𝐷𝐷 𝑅𝑅𝑅𝑅𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝐷𝐷𝐷𝐷 = 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐹𝐹𝐹𝐹𝑜𝑜𝑜𝑜𝐴𝐴𝐴𝐴𝐹𝐹𝐹𝐹𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐹𝐹𝐹𝐹 𝐹𝐹𝐹𝐹𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑑𝑑𝑑𝑑
+ 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑅𝑅𝑅𝑅𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝐷𝐷𝐷𝐷𝐴𝐴𝐴𝐴𝑑𝑑𝑑𝑑𝐷𝐷𝐷𝐷 𝐹𝐹𝐹𝐹𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑑𝑑𝑑𝑑
These delays were measured and the actuator
was controlled by selecting the server properties
(Table 2).
Table 2 - Server properties
Sri Lanka Service
Provider of server
IP
Main Server
Location
Server IP
Server Model
Protocol
WSO2Pvt Ltd
Singapore, 8071 km ahead
from Colombo
admin@18.216.10.83:1883
Apache MQ
MQTT
2.2 Design, 3D Printing & Fabrication of Soft
Bending Actuator
Soft robot actuator design was verified and CAD
models for the molds were created and 3D
printed using Acrylonitrile Butadiene Styrene
(ABS) at 200 °C extruder temperature and the bed
at 60 °C. These molds were used to fabricate the
soft actuator [21].
ENGINEER
Figure 6 - Finite Element Analysis
Applying material data similar to elastomer
materials with engineering properties, mesh,
boundary conditions and loads, the behavior of
58
the actuator was tested, and the results are shown
in Figures 6 and 7.
3.
Results & Analysis
3.1 FE Analysis
Finite element method was applied to find out
the required pressure for maximum bending of
the soft actuator.
(b)
Figure 7 - Graph of angle of bending vs time
Without external loads and other factors, the soft
actuator could reach the full bending at 60 0 (to
touch the ball) with 70 kPa pressure without any
failure of the material and the design. Figure 7
shows the experimental results of the bending
behavior of the soft actuator in Jaffna,
Anuradhapura and Kandy with the simulation
results.
(c)
Figure 8 - Comparison of RTD values
between DG and soft actuator
3.2. Experimental Analysis
Table 3 - RTD values in different distances
RTD values for the corresponding bending
angles were taken over 402 km (distance between
Colombo and Jaffna), 200 km (distance between
Colombo and Anuradhapura) and 133 km
(distance between Colombo and Kandy) and as
shown in Figures 8(a), 8(b) and 8(c), respectively.
4.
Distance between
DG and Soft
actuator (km)
Average
RTD (ms)
402
200
133
710.2
688.23
712.51
Conclusion
The results show the comparison between the
RTD values obtained from two remote areas
Kandy (133 km) and Jaffna (402 km) according to
the behavior of the soft actuator in the central
point (Colombo). It shows some high delays from
Kandy, which is suspected to be attributed to the
mountainous terrain and the rainy climate
present when the data was collected. Also, the
reasons for these variations of the system could
be due to the disturbances or the weakness of the
strength of the communication signal, whereas
(a)
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consequence of insufficient 4G facilities.
In a good communication network, the value of
the end to end delay is half of the RTD value.
However, the quality of service also depends on
the service provider and other aspects.
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Finite element method was used to study the
behavior of the soft bending actuator and the
results show good agreement with the
experimental behavior of the soft finger
fabricated by elastomer rubber material.
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Authors would like to thank the Engineering
Trainees APDT Pathirana and Pradeep
Rathnayake for their valuable assistance in this
project, and would also like to express their
gratitude to WSO2 Pvt. Ltd for providing WSO2
server and its Senior Software Engineer Charitha
Gunathilaka and his expertise whenever needed.
This work was funded by the University
Research Grant of The Open University of Sri
Lanka.
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