Mobile Robots: An Overview of Data and Security

Esmeralda Kadena

, Nguyen Huu Phuoc Dai

and Lourdes Ruiz

Doctoral School on Safety and Security Sciences, Óbuda University, Budapest, Hungary

Keywords: Collection, Communication, Data, Mobile Robots, Security.

Abstract: The field of mobile robotics has become the focus of several types of research for many years. The

revolutionary technology of Wireless Sensor Networks (WSNs) has provided many benefits for the process

of data collection and communication. On the other hand, the network is facing challenges in supporting the

traffic requirements to carry on the data flow generated by the nodes. Hence, the focus of this work is to give

an overview of data processes in mobile robots based on the literature review. At first, we present the

definitions and the most common types of mobile robots. Then, we emphasize the role of sensors and sensor

nodes in WSNs for gathering and communicating the data. In the fourth section, we extend this work by

introducing the main security issues posed to data in mobile robots. Our conclusions are drawn in the end.

As this paper generally describes and points out the main problems related to data in mobile robots, further

analysis is planned for future work.

1 INTRODUCTION TO MOBILE

ROBOTS

Mobile robots are robots that can move from one

place to another place automatically without any

external human assistance. They can be classified as:

▪ Land-based: wheeled robot, tracked robot,

legged robot, manipulator robot;

▪ Air-based: plane, helicopter, quadcopter,

drones;

▪ Water-based: boat, submarine, hybrid, or

stationary robot (arm/manipulator robot)

(Rasam, 2016),

▪ Space-based: Robonaut 1&2, Valkyrie

(Elizabeth Howell, 2017).

Mobile robots offer several benefits such as

working 24/7, accuracy and consistency, working in

harsh environments like in industrial, medical, and

space environment, and job creation (Rachel, 2018).

However, they also have some drawbacks like power

supply, implementing, deploying, maintaining and

repairing costs. They are not intelligent as a human,

dependency on robots, unemployment, and human

fears of robots (Heba Soffar, 2016). This paper briefly

describes data processing and communication in

https://orcid.org/0000-0002-3808-6909

https://orcid.org/0000-0003-1523-0856

https://orcid.org/0000-0002-3649-6226

mobile robots via a meta-analysis of literature

reviews. Moreover, the role of the robot’s sensors and

sensor nodes in WSNs to collect information,

challenges and solutions are emphasized and

discussed. Furthermore, several security issues of

robot’s data transmission are also indicated to draw

users’ attention and increase their security awareness.

2 DATA COLLECTION

Data collection is the process of data gathering from

one or more points for using them at more points

(Weik, 2001). Data can be gathered from different

network stations to process them on a computer or at

a central location.

In the traditional form, data were collected

manually. Such a process has been considered time-

consuming, too long, and the generated data were

limited as well (Swartz et al., 2012). Due to

technological advancements, the process of data

collection has made significant progress. The

development, installation, and integration of wired

and wireless sensors into different kinds of systems,

has provided better results.

Kadena, E., Huu Phuoc Dai, N. and Ruiz, L.

Mobile Robots: An Overview of Data and Security.

DOI: 10.5220/0010174602910299

In Proceedings of the 7th International Conference on Information Systems Security and Privacy (ICISSP 2021), pages 291-299

ISBN: 978-989-758-491-6

291

Wireless Sensor Networks (WSNs) monitor and

communicate the conditions and features of a

physical environment (i.e., acoustic, visual, vibration,

motion, radio, magnetic, heat, light, biological) (Canli

& Khokhar, 2009). Data acquisition and

dissemination protocols in WSNs aim to collect

information from sensor nodes and to forward it then

to the subscribing entities. As a result, the data rate is

achieved while maximizing the lifetime of the overall

network. The gathered information can be data raw or

processed by using typical signal processing

techniques (i.e., filtering, aggregation, event

detection.). During the navigation of ambient data, a

mobile robot follows the steps shown below (Figure

1):

Figure 1: Steps for data collection in mobile robots (Mantha

et al., 2018).

2.1 Sensors

As mobile robots are assigned for several types of

applications, an essential element to achieve their

primary purpose is sensor-guidance (Drunk, 1988).

Sensors used in mobile robots are classified based on

their tasks and working principles.

2.1.1 Navigation Sensors

Navigation is the process of determining and

controlling the position, direction, and speed and

movements of a robot from one point to another

without considering the obstacles (Lobo et al., 2005).

The sensors for navigation are categorized as internal

and external. In external navigation, the most

commonly used sensors are as below.

Laser Range Finders: a sensor used for

determining the distance to an object by using a laser

beam (Eric, 2020). Usually, this technique does not

provide high precision measurements. Thus, it is

replaced by triangulation and similar techniques.

GPS (Global Positioning System): provides

information about latitude, longitude, and altitude

(Xu & Xu, 2016). GPS can be used for static,

kinematic, relative, and multi-receiver positioning.

Some authors have found some problems related to

the use of GPS in mobile robots such as the signal can

be blocked periodically because of foliage and steep

terrain, multi-path interference, and insufficient

position accuracy (Hofmann-Wellenhof et al., 2001).

Therefore, GPS should be combined with other

information.

MMWR (Millimeter-Wave Radars): determine the

range and bearing to a set of beacons that are set up at

known locations (Durrant-Whyte, 1996). Such radars

aim to detect and avoid obstacles. These radars have

full control of the beacons (number and precise

location). Thus, they can be considered more reliable.

Ultrasonic Sensors: range sensors for map

building and collision detection (Kanayama et al.,

1984). Their working principle is based on the

wavelength (Pagac et al., 1996). Such sensors can

offer valuable and useful data when the sound speed

is precisely known. However, there are some

disadvantages: the used wavelengths, when the target

is mirror-like objects, and when the angle between the

normal to the object surface and the sensor direction

is more than 10 degrees. In such conditions, there is

not any significant reflected signal.

Internal navigation is associated with sensors

mounted inside of the robot. This navigation is not

related to environmental features or marks. The most

common types of sensors are as follows.

Encoders: are digital optical devices that convert

motion into digital pulses’ sequence (robotiksistem,

2019). They are used for determining the velocity,

acceleration, or position of a vehicle.

Gyroscopes: are devices that measure the inertial

state of vehicles (Scheding et al., 1997). Due to their

features (non-radiating, non-jammable, and fast),

these sensors provide many advantages, especially for

harsh environmental conditions. They can also

compensate for errors that occur in the odometry

based positioning method. Recently, fiber optic gyros

provide better accuracy, and they have been an

essential solution for navigation in mobile robots

(Pao, 2018).

Potentiometer: is a rotary analog device used in

several electrical and electronic circuits, and that

operates mechanically as a three-terminal

(Electronics Tutorials, 2020). They do not need to

have a power supply or additive circuitry to perform

their position (linear or rotary) function. Due to their

variety, they provide simplification for controlling

and adjusting voltage, current or the biasing, and for

controlling the circuits to obtain a zero condition.

Electronic Compasses: devices that indicate the

yaw heading to an object when they measure the

earth’s magnetic field (Skvortzov et al., 2007). When

the compass is mounted into a vehicle, it shows only

the direction of where the vehicle is headed. In

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292

human-made indoor environments, it can be found a

considerable source of magnetic interference like

reinforced concrete floor and walls, pipes, wiring,

built-in cabling, different metals, and magnetic

objects. The compass can experience magnetic

interference from floor fields when the height of the

compass on the floor is low (Qin et al., 2012).

2.1.2 Sensors for Environment Perception

Environmental perception is a complicated and

complex task of mobile robots (Drunk, 1988). An

important method used for environment perception is

collision sensing (Leng et al., 2016). Robots sense

collision points and direction to avoid collision again,

and then the compliment control comes true. Some of

the most commonly used sensors for environment

perception are presented in the following paragraphs.

Vision Systems: complex systems mounted on

mobile robots. See for more, the system represented

by Eugenio et al. (Eugenio et al., 2007). These

systems primarily aim to capture a very high number

of points in the environment.

Laser-based Range Finding 2D and 3D: scanner

devices that produce a precise image of the

environment (Drunk, 1988). Due to the relatively

high price of 3D lasers, 2D ones have been applied in

many mobile robots, even though they might provide

limited information related to the robot environment.

For instance, a laser ranger at first was designed for

the safety of dangerous areas and as an electronic for

industrial autonomous guided vehicles (SICK AG,

2004). It works based on the time-of-flight principle

and has a single moving part-the the rotating mirror

(Demim et al., 2018). On the other hand, 3D sensors

have more extended capabilities (Generation Robots,

2018). It means that more data are gathered in

multiple dimensions that result in higher

measurement accuracy.

2.2 Sensor Nodes

There are hundreds of thousands of sensor nodes

included in a WSN (Matin & Islam, 2012). Sensor

nodes use radio signals to communicate. A wireless

sensor node is comprised of sensing and computing

devices, radio transceivers, and power components.

They depend on processing speed, storage capacity,

and communication bandwidth level.

After sensor nodes are deployed, their

responsibility is related to organizing by itself an

adequate network infrastructure, usually with multi-

hop communication. Then, the needed information

starts to be collected by onboard sensors. Besides,

sensor devices reply to queries that control sites send

for performing instructions or providing sensing

samples. GPSs and local positioning algorithms can

be used to obtain information regarding location and

position. Actuators can be set into wireless sensor

devices so they can act under specific conditions.

Akkaya and Younis refer more specifically to such

networks by defining and describing them as Wireless

Sensor and Actuator Networks (Akkaya & Younis,

2005).

Due to the improvements in information accuracy,

the significance of WSNs has been increased (Chong

& Kumar, 2003). The tasks of sensor nodes are to

monitor the events that are happening within their

sensing region, to collect the data to a sink node or

base station, and to give meaning to the available

information into the sink node. Then, users can get

the data provided into the sink node and monitor the

sensing regions’ status. The use of WSNs can be

found in many applications like surveillance, health

monitoring, and investigations related to harsh

physical environments (Mainwaring et al., 2002),

(Galstyan et al., 2004).

2.2.1 Structure

The components of a sensor node are sensing,

processing, transceiver, and power unit (Akyildiz et

al., 2002).

Mobile sensor nodes can change the position

autonomously and are subject to mission

requirements. The benefits of them are related to the

dynamic way they adjust network topology and to the

promotion of sensor networks performance. The areas

in which sensor nodes operate are typical disaster

ones or harsh, remote environments where people

face difficulties (Ssu et al., 2005):

Also, mobile sensors have the auto-refresh ability

that helps to troubles and issues within a sensor

network (Mora Vargas et al., 2006). Tanaka et al.

proposed a dispersed algorithm to contribute to such

confronts (Tanaka et al., 2012).

2.2.2 Data Collection from Mobile Nodes

To collect data, a mobile collector can go very close

to a node. Thus, the node does not need a powerful

transceiver to communicate with the mobile collector

but only to wait until the collector goes close enough

(Zheng et al., 2017). Data collection in WSNs with a

mobile sink node consists of the following steps

(R.Wankhade & Morris, 2013):

▪ Discovery: mobility independent and

knowledge base;

Mobile Robots: An Overview of Data and Security

293

▪ Data Transfer: joint discovery and transfer of

data;

▪ Routing: flat and proxy-based;

▪ Motion Control: trajectory, static, dynamic,

speed, and hybrid.

Since the nodes communicate only with the

mobile collector and not with the other nodes, they do

not need to have connectivity in the whole network

(Zhang et al., 2015), (Nguyen & Teague, 2015).

Other authors have worked on mobile elements

for reducing and set of scales in WSNs, but yet the

compilation of data can elevate (Liang He et al.,

2011). Hence, concerns related to mobile elements

such as the way they navigate during the detected

field and when they gather data from the sensors,

have had attention and consideration from the

researchers (Z. Wang et al., 2011). Ping et al. suggest

that if the mobile antennas that meet data in short-

range transportations will be used to gather data in

WSNs, considerable improvement can be achieved

(Ping et al., 2009).

2.3 Challenges

Some of the challenges related to data collection in

mobile robots are listed as follows.

High Costs: The costs depend on the surface of

buildings and, as a consequence on the number of

places that must be monitored. Thus, the material and

installation process can require a considerable

amount of money (Demirbas, 2005).

Complex Design Requirements: Disturbances in

indoor environments should be taken into

consideration. They have a significant impact on the

process design of the networks (F. Wang et al., 2010).

Supervision: Usually, sensors are installed in

several locations, and there are several. Because of

their number, they might need continuous monitoring

against the threats they are posed from outsiders (F.

Wang et al., 2010).

Maintenance: The calibration and maintenance

process of the wireless sensors should be intense.

Limited Coverage: Because of the high costs

involved, the space that can be monitored is relatively

limited (Demirbas, 2005).

Other Challenges: WSs face issues from power

consumption, scalability, and storage capacities.

These influence the amount and quality of the data

that can be collected (Raftery et al., 2011). Moreover,

the terrain or the place where the sensors are placed

plays a significant role. For instance, if the sensors are

placed in heritage buildings, they can have a

damaging impact on the underlying surface as the

historical value of the place can be affected (Raffler

et al., 2015).

3 DATA COMMUNICATION

Data communication is defined as the transmission of

digital data such as numeric data, text, voice, video,

photos between a source and a receiver (Techopedia,

2017). Its purpose is not the generation of data nor

the outcome of the data transmitted but the transfer

method and the data preservation during the

transmission process (Data Communication -

Computer Networking Concepts, 2019).

3.1 Types of Communication in Mobile

Robots

Communication plays an important role to fulfill

tasks in real-life processes. Mobile robots can use

communications in the following situations presented

below (Gage, 1997):

Robot and User Control Station: For example, in

surveillance systems, the data collected comprises

alarms or alerts, which are the result of the

information acquired by the sensors. As a result, these

alarms indicate a threat. Thus, the robot sends

additional information such as images, audio, or

videos in order to assess the problem.

Robots and Multi-robot System: Communication

between robots and a multi-robot system is used for

tasks such as supporting sensor data fusion, cueing

from sensor to sensor, collaboration, and coordination

of actions between robots and letting a robot act as a

communications relay among other robots or user

stations.

Robot System and External clients:

Communication between robots and external sources

serve for transferring sensor or processed data from

the robot to an external client such as military

officers.

Robot and Developer: The communication

between the robot and a system developer is

necessary for decreasing technical risks, boost

productivity at the implementation phase by

deploying software downloads and debugging tools

to validate hardware and software. The

communication will be able to allow developers to

design, deploy, and integrate the software with the

robot remotely.

Consequently, mobile robot communication can

be envisioned for several applications, as showed in

Figure 2. Robots can be teleoperated by a human or

software which sends commands to the robot and

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receives data. Hence, low latency communication via

the Internet is needed. Robots can work in a multi-

robot system where low-power and long-range

wireless communication is required. Remote sensing

robots also need long-range wireless communication.

Moreover, robots’ access to the Internet via a

reliable communication link can enable uploading

their processing tasks to the cloud, which can upgrade

their computing and physical capabilities.

Figure 2: Mobile Robot Applications (Barriquello et al.,

2018).

3.2 Communication Process

Three elements compose data communication within

the mobile robot and its surroundings (Barriquello et

al., 2018): awareness, processing and cognition, and

action.

Awareness involves the data acquisition of the

environment, the robot, and the relation between the

robot and the surroundings. The information acquired

is processed and sent to the actuators, which are in

charge of the robot’s motion. Once the data, such as

the direction, destination, and purpose of the robot are

established, the robot’s cognition needs to arrange a

plan on how the robot will achieve its purpose.

The cognition and control system responsible for

the decision making and the deployment the robot

uses in order to attain its goals. Additionally, the

control system integrates the input data and the

robot’s movements. Cognitive models are necessary

for a mobile robot. They are expected to represent the

robot, the environment, and the interaction between

them. Different areas work in a cognitive model. For

example, computer vision and pattern identification

are useful for keeping track of objects; and map

algorithms are utilized to create maps of the

surroundings.

Artificial intelligence algorithms, such as motion

planning, are employed to manage the robot’s

interactions. Furthermore, it is anticipated that in the

coming years, artificial intelligence will be mainly

used for managing the information collected by the

robot and the task given to it.

3.3 Internet Data Communication

The Internet as a communication channel has non-

deterministic characteristics, depending on the

network load. It is a non-expensive and readily

available communication tool. However, it has

significant limitations for robotic systems due to the

restricted bandwidth, transmission delays, and data

loss that impact the robots and system performance.

The connection performance depends on the

speed and reliability of the transmitted data over that

connection. In the case of the Internet, speed and

reliability cannot be measured (Khamis et al., 2003).

Moreover, the upcoming 5G telecommunications

will open up a variety of opportunities regarding

mobile robotic applications in numerous fields such

as education, ecology, medicine, agriculture,

manufacturing, and more industries (Durmus &

Gunes, 2019). These applications require remote

interaction in which the human and the robot are

physically separated but are connected by telematics

3.4 Challenges

Frequency communication is used for rescue and

relief purposes (Greer et al., 2002). These robots use

Industrial, Scientific, and Medical (ISM) bands,

which are unlicensed frequencies and present some

disadvantages. Communication can fail due to

interferences since the bands are not licensed. The

output power in the device and the control unit can be

restricted, preventing signals from other units.

Efficiency in the transmission is affected when

higher frequencies are used. Higher frequencies can

penetrate more dense materials, such as in buildings.

However, small elements such as dust resonate at

high frequencies absorbing the signal. It is suggested

to use a frequency in the middle of the two extremes

that optimize communication. UHF frequencies are

recommended since they need low power output and

have excellent signal penetration characteristics.

Mobile robots controlled over the Internet pose

several challenges such as internet transmission delays,

delay jitter, and a non- guaranteed bandwidth in

contrast with other communication systems in which

there are constant delays and a limited but guaranteed

bandwidth. These issues can lead to system perfor-

mance degradation and can impact on the stability if

they are not taken into consideration during the design

and deployment of the system (Alves et al., 2000).

Mobile Robots: An Overview of Data and Security

295

As a solution is suggested to eliminate human

operators from the control loop, implement high local

intelligence and reactive behavior into the robots.

Hence, mobile robots will autonomously manage

real-world uncertainty and network delays.

Furthermore, an intuitive user interface is needed for

facilitating non trained staff in the remote control of

the robot. The whole system should be reliable so that

the users can access it at any time without the

necessity of human interaction (Hu et al., n.d.).

TCP and UDP are the transport protocols used for

data communication among Internet-based robots. In

this case, the exchange of information between the

operator and the robot must not have delays. TCP is

utilized for reliable static data communication such as

emails and files in low- bandwidth. It guarantees the

retransmission of a lost packet, which causes

significant delays and efficiency reduction. UDP

reduces delays, but it is not able to cope with extra

bandwidth and network congestion.

Consequently, TCP and UDP are not suggested

for teleoperation (Kazala et al., 2015). As a solution,

a trinomial protocol for robotic internet systems is

proposed. It is a source-based protocol that displays a

similar performance to UDP concerning delays, delay

jitter, and packet loss rate. Its steady-state and the

transmission rate are better than TCP. It quickly

adapts to network bandwidth variation (Xiaoping Liu

et al., 2003), (Schiøler et al., 2012).

4 SECURITY ISSUES

4.1 Security Threats

Data transmission between robots and base stations

via the network needs to go through computers and

routers such as wireless hotspots. Due to this reason,

it can be targeted by a third party or a hacker. Several

threats in the network traffic include:

Computer Viruses: small software can disable the

security settings, corrupt, and steal data from the

computer, including personal information like

passwords, or deleting everything on the hard drive

(Team, 2018).

Rogue Security Software: a malicious software

that can mislead users to think that there are some

computer antivirus scanners (Cova et al., 2009) on

their computer or their systems and the security

firewall or antivirus software are not up to date.

Trojan Horse: malware or malicious code, which

trick users into running it by opening an attachment in

the email or clicking on false advertisement. When a

trojan horse is inside the system, it can save passwords

by using keystroke logging or hacking webcam and

stealing sensitive data on the computer/system.

Eavesdropping: information remains flawless,

but its privacy is compromised. Someone could

capture sensitive conversation or intercept classified

information during transmission.

Tampering: information during transferring is

changed or replaced and then sent to the recipient.

Impersonation: information passes to a person

who poses as the intended recipient. Impersonation

can take two forms: spoofing (a person can pretend to

have the email address of another person, or a

computer can identify itself as another website when

it is not) and misrepresentation (a person or an

organization can misrepresent itself).

Adware or Spyware: recognized as any software

that is designed to track users’ data surfing habits.

Adware aims to collect consent data. Spyware is

similar to adware, but it is installed on a computer

without notice. It may include keyloggers to take

personal information, including email addresses,

passwords, and credit card numbers (Team, 2018).

Phishing: a social engineering method aiming to

get sensitive data such as passwords, usernames,

credit card numbers (Figure 3). There are several

types of phishing attacks, such as spear phishing,

clone phishing, and whaling (Cloudflare, 2020).

Figure 3: Phishing attack (Cloudflare, 2020).

DDOS Attack: the attackers break online devices

networks (i.e., computers or other IoT devices), make

them as bots or zombies, and gain control over a

target. When a botnet has been set up, the adversaries

are able to directly send updated instructions to each

bot through a method of remote control. As a result,

the victims’ network will overflow its capacity and

lead to the servers’ or networks’ denial of service.

4.2 Security Attacks

External Attacks: They occur by outside network

attackers when they do not have any information

about the network system. Also, it is related to several

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layers of the OSI model, such as the physical layer,

data link layer, network layer, and transport layer

(Puthal, 2012).

Internal Attacks: They can take place due to the

flaws in networking protocols or weaknesses in

software that integrate networking protocols. These

intrusions focus on the network and transport layer of

the OSI layer (Kamal & Issac, 2007).

Man in the Middle Attack: It happens when an

attacker uses some techniques to put someone in the

middle of a conversation between a user and an

application to eavesdrop or capture the information

(Imperva, 2020). The main goal of this attack is to

steal personal information, for example, identity theft,

passwords to target Advanced Persistent Threat

(APT) (Figure 4).

Figure 4: Man in the middle attack (Imperva, 2020).

Furthermore, MITM aims to steal the session

through packet sniffer to gain control in some layers,

such as Application, Presentation, Transport, and

Datalink in the OSI model. MITM has two major

distinct stages: interception (Ip spoofing, ARP

spoofing, and DNS spoofing) and decryption

(HTTPS spoofing, SSL beast, SSL hijacking, and

SSL stripping).

5 CONCLUSIONS

This paper presented an overview of mobile robots by

emphasizing the importance of data collection,

communication, and security. It was shown that the

most significant devices are sensors assigned for

different kinds of applications. Also, it was shed light

on the significance of WSNs and sensor nodes. Then,

we explained and highlighted the data

communication procedures as an essential element

for fulfilling the tasks in the real-life. Communication

between users and robots or within robot systems is

critical to assure the effectiveness and the correct

fulfilment of the robot’s task. It plays a crucial role in

the mobile robot’s performance. In the last part, we

described the security threats and issues concerning

data collection and communication.

The scientific data collected in this work suggests

that due to the complexity and different environments

where mobile robots operate, careful attention must

be paid in reducing (if not eliminating) the challenges

of data collection and communication. Also, we

propose that future research should be taken in the

area of security risks of data transmission. We believe

that our research will serve as a baseline for further

investigations in the field of mobile robots.

ACKNOWLEDGEMENTS

This article is supported by national grant “VKE-

2017-00031” on High Precision Surface Control

Robot Prototype.

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