Towards a Cultural Perspective on Human-Robot Interaction

Bhavishya Swami

1 a

, Jeshwitha Jesus Raja

1 b

, Meenakshi Manjunath

1 c

, Amruta Rout

2 d

and

Marian Daun

1 e

Center for Robotics, Technical University of Applied Sciences W

urzburg-Schweinfurt, Schweinfurt, Germany

Department of Mechanical and Automobile Engineering, CHRIST University, Bangalore, India

Keywords:

Human-Robot Interaction, Conceptual Framework, Cultural Inﬂuence.

Abstract:

Human–robot interaction is a rapidly emerging ﬁeld whose scope and deﬁnition remain diffuse due to its broad

application across diverse robotics domains. Research in human–robot interaction typically moves beyond

simple input–output interfaces to explore more complex interactions, such as physical collaboration between

humans and robots. Consequently, various perspectives on human–robot interaction—ranging from techno-

logical considerations and cooperation modalities to trust and safety—have proliferated in both research and

practice. Although the priorities in human–robot interaction research often reﬂect industry demands and so-

cietal values, the cultural context in which these priorities evolve has received limited attention. In particular,

how different countries’ expectations shape the perceived importance of human–robot interaction perspectives

remains under-explored. A deeper understanding of these cross-cultural differences can foster a global view of

human–robot interaction and support the transfer of best practices across borders. Therefore, this paper exam-

ines representative case studies from Germany and India, highlighting key divergences in how human–robot

interaction is deﬁned and approached in different cultural and industrial contexts.

1 INTRODUCTION

Human-robot interaction (HRI) is a growing ﬁeld

gaining importance, for instance, in the context of in-

dustry 4.0 (Vemuri and Thaneeru, 2023; Daun et al.,

2023) or the introduction of advanced service robots

in daily life (Fukuda et al., 2011). Thus, research in

HRI stems from different robot system types. In ad-

dition, the multidisciplinary nature of HRI broadens

the ﬁeld further. From a software engineering per-

spective, this variety of HRI and the resulting lack of

a clear deﬁnition, makes it hard to propose develop-

ment approaches properly considering HRI aspects of

robotic software. To help in this, taxonomies and clas-

siﬁcations of HRI systems are used to structure the

ﬁeld (e.g., (Onnasch and Roesler, 2021)).

Unfortunately, existing classiﬁcations primarily

focus on the technical aspects of HRI systems (e.g.,

(Agah, 2000)), with additional emphasis at times on

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https://orcid.org/0000-0002-9156-9731

the social aspects of HRI (e.g., (Gervasi et al., 2020)),

or speciﬁc factors such as safety (e.g., (Zacharaki

et al., 2020; Manjunath et al., 2024)) and security

(e.g., (Akalin et al., 2023)). However, all these dimen-

sions are not independent of one-another, and, thus,

the interrelations between these are currently not well

reﬂected. For instance, the use of natural language

processing approaches for speech recognition (e.g.,

(Wuth et al., 2021)) is impacted by trust in the com-

pany (e.g., (Song and Kim, 2022)).

A challenge in deﬁning a conceptual framework

that accounts for the inﬂuence of social factors on

technological components is the limited understand-

ing of cultural inﬂuences. With HRI research being

conducted around the world, the approaches are of-

tentimes not transferable from one country to another

due to a difference in social factors rooted in differ-

ent cultures. For instance, the attitude towards the

strictness and importance of safety and security dif-

fers between countries (cf. (Weng et al., 2009)). Data

protection might be a severe part of cultural life, for

example, as shown by the European Union’s data pro-

tection laws, which limits the use of technology in

some countries.

782

Swami, B., Jesus Raja, J., Manjunath, M., Rout, A. and Daun, M.

Towards a Cultural Perspective on Human-Robot Interaction.

DOI: 10.5220/0013471900003928

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2025), pages 782-789

ISBN: 978-989-758-742-9; ISSN: 2184-4895

Therefore, in this paper, we argue that there is a

need for a conceptual framework of HRI that not only

considers and brings together technological and so-

cial factors, but explicitly takes a cultural perspective

on HRI into account. Such a conceptual framework

on HRI will allow for better classiﬁcation and com-

parison of approaches, as well as supporting trans-

ferability of approaches from one country’s cultural

background to another. In this paper, we exemplarily

investigate the need for a conceptual framework con-

sidering case examples from Germany and India. In

doing so, we show the need to a) consider a cultural

perspective for HRI, and b) consider the inﬂuence of

culture on the interrelation between social factors and

technological components of HRI.

The paper is outlined as follows: Section 2 intro-

duces HRI and reviews existing taxonomies and re-

search related to culture in HRI. Section 3 presents

the initial conceptual framework for HRI, differenti-

ating between technical, social, and cultural perspec-

tives and their interrelations. Section 4 discusses a

case study from Germany and India. Finally, Section

5 concludes the paper.

2 RELATED WORK

2.1 Culture in HRI Research

The concept of culture has been extensively stud-

ied across disciplines, with each focusing on differ-

ent aspects such as shared customs, rules, attitudes,

and social practices (Koltko-Rivera, 2004). It encom-

passes diverse elements, including traditions, tech-

nologies, and collective behaviors (Matsumoto and

Juang, 1996). In computing, culture concerns en-

abling users to engage through the values and charac-

teristics of their cultural identity (Rauterberg, 2006).

Cultural values inﬂuence not only the develop-

ment of robots, but also the reciprocal impact of

robotic cultural values on human behavior (Samani

et al., 2013), further contributing to trust and trustwor-

thiness in HRI. Cultural studies also contribute to en-

suring effective and meaningful interactions between

humans and robots (Keay, 2012). A study by Evers et

al. (Evers et al., 2008) examined how cultural frame-

works shape user behavior in HRI by comparing re-

lational and group self-construal, highlighting the in-

ﬂuence of culture and background on these interac-

tions. Building on this, Salem et al. (Salem et al.,

2014) explored politeness, showing that user percep-

tions of robots are inﬂuenced by social norms and ex-

pectations. Additionally, cultural norms impact user

comfort levels regarding proxemics, or the spatial be-

havior of robots (Joosse et al., 2014).

Social robots are designed to interact with peo-

ple in a natural, interpersonal manner, unlike robots

in industries where their actions are predetermined,

and the environment is controlled. Social robots are

meant to achieve positive outcomes in diverse appli-

cations such as education, health, quality of life, en-

tertainment, communication, and tasks requiring col-

laborative teamwork (Breazeal et al., 2016). These

applications contain global implications and in order

to enhance its global adoption, these robots should be

culturally competent (Lim et al., 2021). A case study

by Bennett et al. (Bennett et al., 2022) compares the

use of robotic companion pets in South Korea and

the United States, highlighting divergent cultural atti-

tudes toward robot anthropomorphization and utility.

Robots can also represent cultural emotions and thus

provide a framework for embedding culturally spe-

ciﬁc cues in robot designs (Dang et al., 2017). This

aligns with broader discussions on the ethical and

conceptual fragmentation of cultural robotics (Man-

souri and Taylor, 2024; Bruno et al., 2017).

In the context of WEIRD (Western, Educated, In-

dustrialized, Rich, and Democratic) societies, HRI

still lacks diversity (Seaborn et al., 2023). Cultural

contexts play a crucial role, as they vary signiﬁ-

cantly across different cultures and must be studied to

promote inclusivity. A dynamic and adaptable HRI

system that incorporates user-speciﬁc cultural traits

can enable the development of culturally competent

robots (Bruno et al., 2017). Additionally, social psy-

chological theories provide a theoretical foundation

for understanding the cultural dimensions of human-

robot relationships (Smith et al., 2021).

These studies highlight the importance of culture

in shaping robotic behavior and interaction channels

to align with user expectations. Therefore, they can be

taken to advocate the need for a cultural dimension in

HRI research. However, these studies only investigate

the inﬂuence of culture on direct interaction between

human and robot. In contrast to our approach, they do

not consider cultural attitudes towards the use of tech-

nological components of HRI. Thereby, we aim at ex-

plaining country-speciﬁc differences in HRI research

which allows for comparability and transferability of

HRI research between different cultural contexts.

2.2 Existing Classiﬁcations

Based on the nature of the work performed, the type

of contact, and the restrictions of the workspace,

HRI can be categorized into different types. Refer-

ring to Bauer et al.’s (Bauer et al., 2016) catego-

rization of interaction types—which is widely used

Towards a Cultural Perspective on Human-Robot Interaction

783

in the ﬁeld and covers numerous modalities—these

types include Human-Robot Cell, Human-Robot Co-

existence, Human-Robot Synchronization, Human-

Robot Cooperation, and Human-Robot Collaboration.

These types differ based on varying degrees of auton-

omy, which inﬂuence the dependencies between hu-

mans and robots (Jesus Raja et al., 2024).

In (Onnasch and Roesler, 2021), a taxonomy for

structuring and analyzing HRI was proposed which

contains emphasizing factors such as interaction

modalities, levels of autonomy, and user roles. This

taxonomy addresses the varying degrees to which hu-

mans and robots can collaborate—ranging from sim-

ple, sequential interactions to highly interdependent,

synchronized tasks. The taxonomy categorizes HRI

into three main types: Classiﬁcation of interaction,

Classiﬁcation of robot and Classiﬁcation of the team.

Gervasi et al. (Gervasi et al., 2020) proposed a

conceptual framework to evaluate human-robot col-

laboration, comprising eight latent dimensions: au-

tonomy, information exchange, team organization,

adaptivity and training, task, human factors, ethics,

and cybersecurity. Within this framework, human

factors include elements such as workload, trust,

robot morphology, physical ergonomics, and usabil-

ity, while ethics encompasses aspects like social im-

pact and social acceptance. Notably, culture is not ex-

plicitly included as a dimension, despite its inﬂuence

on factors such as social acceptance, trust, and social

impact. This omission highlights a gap in addressing

cultural considerations.

3 CONCEPTUAL FRAMEWORK

The currently existing classiﬁcations in HRI primarily

consist of technical factors, such as degrees of auton-

omy, sensing capabilities, and human-machine inter-

face designs, and, to some extent, social aspects, such

as trust and acceptance. The incorporation of cultural

aspects, which inﬂuence the social aspects, is still

lacking. Therefore, we propose a conceptual frame-

work explaining the inﬂuence of cultural aspects on

social and technical dimensions of HRI. Figure 1 il-

lustrates the three perspectives, along with examples

and their interrelationships.

3.1 Technical Perspective

In the ﬁeld of HRI, the technical perspective rep-

resents the infrastructure that allows interaction be-

tween humans and robotic systems. This perspec-

tive encompasses the essential hardware and software

components, ranging from sensing mechanisms to ad-

vanced computational architectures, that collectively

facilitate robot functionality. By examining these

technical elements, we can better understand what

components are required for the development of the

robotic system and how and why these components

are inﬂuenced by social and cultural aspects. For in-

stance, in collaborative manufacturing environments,

the integration of advanced perception systems with

precise motion control algorithms enables robots to

work safely alongside human operators while main-

taining optimal performance. In Figure 1, the block

labeled

⃝ provides a list of aspects from the techni-

cal perspective, for example:

• Sensing Mechanisms: These include environ-

mental sensors, cameras, and detection systems

that allow robots to perceive and understand their

surroundings, enabling safe and effective interac-

tion with humans.

• Actuation Systems: Components that enable

robots to interact with their environment by con-

verting energy into motion. This conversion pro-

cess allows robots to perform tasks ranging from

simple to complex. Actuators are the driving force

behind a robot’s ability to move.

• Computational Processing Units: High-

performance computing architectures handle

complex calculations and real-time decision-

making processes when the robot works.

• Interface Modalities: Robots communicate

with humans through various channels includ-

ing touchscreens, voice commands, and gesture

recognition systems. These different interaction

methods ensure that humans can communicate

naturally and effectively with robotic systems.

• Motion Control Algorithms: The smooth and

precise movements of robots are guided through

preplanned and executed trajectories. These algo-

rithms ensure robots move safely around humans

while efﬁciently completing their tasks.

• Perception Systems: Advanced software that

processes the data from various sensors to help

robots understand their environment. This

includes recognizing objects, tracking human

movements, and understanding spatial relation-

ships in the workspace.

• Human-Machine Interfaces: The points of in-

teraction between humans and robots are designed

to be intuitive and user-friendly. These interfaces

allow operators to communicate their intentions

and understand robot status easily.

• Communication Protocols: Various components

of a robotic system exchange information through

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784

Figure 1: Conceptual HRI Framework Differentiating between Three Major Perspectives and Their Interrelations.

standardized methods. These protocols ensure re-

liable and efﬁcient data ﬂow, enabling coordinated

operation of all system parts.

3.2 Social Perspective

HRI fundamentally relies on understanding and ad-

dressing social dynamics between users and robotic

systems. For instance, in healthcare, robots must es-

tablish trust and maintain user comfort while perform-

ing tasks. The social perspective (labeled

⃝ in Fig-

ure 1) examines how humans perceive and respond to

robotic interactions, considering factors from initial

acceptance to long-term collaboration patterns. Im-

portant aspects of the social perspective contain:

• User Acceptance: This aspect tells how differ-

ent users adapt to and accept robotic systems, and

how this varies based on their experience and con-

text. For instance, healthcare workers may readily

accept assistive robots when they clearly under-

stand the beneﬁts and receive proper training.

• Trust Formation: Building trust between hu-

mans and robots happens through consistent and

transparent robot behavior. When robots commu-

nicate their intentions clearly and perform reli-

ably, users develop conﬁdence in working along-

side them.

• Psychological Comfort: The level of comfort

humans feel around robots depends on factors

like robot movement, speed, proximity, and pre-

dictability. Careful consideration of these ele-

ments ensures positively perceived HRIs.

• Social Dynamics: The way humans and robots

interact creates unique social patterns that evolve

over time. Understanding these dynamics helps in

designing more effective collaborative scenarios.

• User Experience: The overall interaction experi-

ence must be intuitive and satisfying for different

user groups. This includes various factors from

interface design to robot responsiveness.

• Interaction Paradigms: This aspect tells us

how robots behave in different social situations.

This includes determining when robots should be

proactive versus passive in their interactions.

• Safety: Beyond physical safety, ensuring that

users feel psychologically secure working with

robots is crucial. This encompasses both actual

and perceived safety measures.

• Ethics: Robots must operate within clear ethical

guidelines that respect human values and rights.

This includes considerations of privacy, auton-

omy, and fair treatment.

3.3 Cultural Perspective

The technical perspective represents the physical in-

frastructure enabling interaction between humans and

robotic systems, while the social perspective ad-

dresses the dynamics of these interactions. The cul-

tural perspective (labeled

⃝ in Figure 1) inﬂuences

both the technical and social aspects. This inﬂuence

on the technical aspects shapes the reﬁnement of tech-

nical components that constitutes a robotic system.

It highlights how cultural factors impact robot de-

sign, behavior, and acceptance across different con-

texts and regions. Important cultural aspects include:

• Cultural Values: Different societies hold varying

beliefs about automation and HRI.

Towards a Cultural Perspective on Human-Robot Interaction

785

• Societal Norms: Acceptable robot behavior

varies across cultures, from communication styles

to physical proximity.

• Traditional Practices: Considering local cus-

toms and traditions can make robots user-friendly,

gaining user acceptance. For example, greeting

the human while passing by can have a positive

impact on the human.

• Regulations: Different regions have varying legal

requirements for robot deployment. These regula-

tions shape technical implementations and opera-

tional parameters.

• Privacy Expectations: Cultural attitudes toward

privacy affect how robots should handle personal

information and maintain appropriate boundaries.

• Safety Standards: Regional differences in safety

expectations require adaptable robot behavior and

safety protocols.

• Communication Preferences: The way robots

communicate must align with local customs and

preferences, from language use to non-verbal

cues. For example, colors differ based on cultural

preferences or professional rules.

• Technological Acceptance: Different cultures

show varying levels of openness to robotic tech-

nologies, affecting implementation strategies.

3.4 Technical-Social Interrelations

The interrelation between technical capabilities and

social requirements (labeled

⃝ in Figure 1) creates

crucial relationships that shape effective HRI imple-

mentation. For instance, in collaborative manufac-

turing or healthcare robotics, we observe how tech-

nical features must adapt to social needs, ensuring

both functional efﬁciency and user acceptance. The

following aspects highlight key areas where technical

and social interdependencies shape robot design and

functionality:

• Interaction Modalities: The way technical inter-

faces adapt to different user preferences impacts

acceptance and usability. For example, elderly

users might prefer simple voice commands, while

industrial workers may favor touchscreen inter-

faces for precise control.

• Robot Behaviors: The technical implementation

of motion control systems must consider social

factors like user comfort and safety. This includes

the robot adjusting its speed and maintaining ap-

propriate distances to humans.

• Communication Protocols: Technical feedback

systems inﬂuence trust development through clear

and consistent communication. Robots signaling

their next actions through visual or auditory cues

help users understand and predict robot behavior.

• Motion Planning Systems: How robots move

aligns with human psychological comfort. This

includes smooth trajectory adjustments when ap-

proaching humans and predictable movement pat-

terns in shared spaces. Additionally, user comfort

and safety concerns also inﬂuence the way motion

control systems are implemented.

3.5 Cultural-Social Interrelations

The relationship between social interaction patterns

and cultural norms (labeled

⃝ in Figure 1) inﬂuences

how robots should behave in different societies. Un-

derstanding these connections is crucial for develop-

ing robots that can operate effectively across diverse

cultural contexts. The following aspects highlight

key areas where cultural and social interdependencies

shape robot design and functionality:

• Cultural Attitudes: Social acceptance of robots

varies signiﬁcantly across cultures, affecting how

users prefer to interact with them. Some societies

readily accept robots in care roles, while others

prefer limiting them to industrial applications.

• Risk Protocols: Safety measures must align with

cultural risk tolerance levels. This includes adapt-

ing robot behavior and safety protocols to match

local expectations and norms.

• Social Interaction Designs: Robot interaction

patterns need to reﬂect local communication

styles and customs. This affects, e.g., personal

space maintenance or communication timings.

• Privacy Mechanisms: Trust-building approaches

must consider cultural privacy expectations. This

inﬂuences how robots collect, handle, and com-

municate about user data.

3.6 Cultural-Technical Interrelations

The inﬂuence of cultural requirements on technical

implementations (

⃝ in Figure 1) shapes how robotic

systems are developed and deployed across different

regions. This relationship ensures that technical solu-

tions remain culturally appropriate and effective. The

following aspects highlight key areas where technical

and cultural interdependencies shape robot design and

functionality:

• Regulations: Technical control systems must

adapt to meet varying geographical safety and op-

erational requirements. This includes different

safety protocols, standards, and certiﬁcation.

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786

• Data Protocols: Robots should process and store

information to align with local privacy standards

and cultural expectations about data handling.

• Natural Language Processing Systems: Lan-

guage processing capabilities must account for

cultural communication patterns, including for-

mal versus informal speech and non-verbal cues.

• Cultural Contexts: Technical development pri-

orities should reﬂect local values and needs, en-

suring that robot capabilities align with cultural

expectations and practices.

4 CASE EXAMPLE

The HRI assembly process used is a sorting pro-

cess performed collaboratively by humans and robots,

involving tasks such as categorizing, scanning, and

transporting. The cobot picks and places packages,

scans barcodes, and transports them to the desig-

nated zone. Humans handle irregularly shaped pack-

ages and resolve ambiguities, such as categorizing

new or unidentiﬁable items. The cobot operates in

close proximity to humans while adhering to strict

safety protocols to ensure smooth interaction. Figure

2 shows the technical, the social and cultural aspects

for India and Germany respectively. The ﬁgure shows

how the aspects differ signiﬁcantly between the two

countries.

For example, in Germany, the technical aspect of

“advanced sensors and high-precision equipment” is

supported by the social aspect of a “technology-ﬁrst

mindset,” which reﬂects how Germans prioritize in-

novation and quality. This social factor is further in-

ﬂuenced by the cultural emphasis on “precision and

efﬁciency,” a value that strongly shapes the work cul-

ture of Germany. In contrast, in India, the techni-

cal implementation of “semi-automated ﬂexible sys-

tems” is shaped by the social focus on “collabora-

tive, community-based dynamics,” which stems from

the cultural emphasis on “community and adaptabil-

ity.” India, being a labor-intensive country, necessi-

tates having a semi-automated system rather than a

completely automated one, allowing robots to work

alongside humans.

This systematic progression from cultural to so-

cial to technical aspects is evident in many scenarios

illustrated in Figure 2. For instance, standardized in-

terfaces and fully automated systems align with Ger-

many’s social emphasis on efﬁciency-focused user

experience and certiﬁcation-based trust formation is

rooted in process-oriented cultural norms. Similarly,

the Indian approach of employing user-friendly inter-

faces and balanced automation with manual override

capabilities highlights how Indian manufacturing pri-

oritizes workforce diversity while embracing techno-

logical advancement.

However, the inﬂuence of culture on technical as-

pects does not always pass through social factors and

can directly shape technical implementations. For ex-

ample, in German manufacturing, the cultural foun-

dation of “process-oriented work culture” and “com-

prehensive guidelines” directly shapes the technical

aspect of “highly structured, well-documented sys-

tems.” In the Indian context, the cultural aspect of

“ﬂexible work approaches” directly impacts techni-

cal solutions, resulting in “simple, user-friendly in-

terfaces.” This cultural-technical relationship is fur-

ther exempliﬁed by the cultural emphasis on blending

modern and traditional methods, which translates into

adaptable, multilingual support systems to accommo-

date the diverse languages and cultures of each In-

dian state, as well as balanced automation solutions.

These examples demonstrate how cultural values such

as workforce diversity and adaptability directly shape

technical implementations in Indian manufacturing

settings.

The interdependencies shown for both Germany

and India are not one-to-one; a single cultural aspect

can inﬂuence multiple technical aspects, and a single

technical aspect can also be shaped by multiple cul-

tural factors. These examples highlight how cultural

differences, which are contrasting in nature for both

countries, shape perceptions and priorities, thereby

inﬂuencing both social dynamics and technical imple-

mentations. While Germany and India differ in social

aspects, these differences stem from their distinct cul-

tural foundations.

Robots in India are often designed to assist hu-

mans in manual tasks rather than replace them en-

tirely (Goodrich et al., 2008). Regarding cultural ac-

ceptance, perspectives in India vary based on socio-

economic factors and exposure to technology. Ur-

ban populations generally have welcoming and in-

tegrative views towards robots, while rural commu-

nities exhibit more diverse perceptions (Deshmukh

et al., 2018). For the Indian market, addressing so-

cietal concerns such as job displacement is critical.

Robots in India are designed to complement human

labor, which has fostered acceptance across diverse

communities (Haring et al., 2019). This emphasizes

the profound impact of cultural factors on the social

and technical dimensions of HRI. In contrast, Robots

in Germany are predominantly designed to meet high-

quality standards, adhering to the country’s rigorous

safety norms. In industrial settings, the focus is on

achieving precision and maximizing production with

minimal human involvement.

Towards a Cultural Perspective on Human-Robot Interaction

787

Figure 2: Conceptual HRI Framework: Comparative Overview of Indian and German Perspectives.

5 CONCLUSION

HRI continues to evolve as a multidisciplinary ﬁeld,

providing innovative solutions to complex tasks that

require collaboration between humans and robots.

While HRI has seen signiﬁcant research, especially

for the technical and social aspects, the inﬂuence of

cultural aspects still remains under-explored. This pa-

per addressed this gap by examining the cultural, so-

cial, and technical interdependencies in HRI through

a comparative case study of Germany and India.

The ﬁndings reveal that cultural values play a piv-

otal role in shaping key aspects of HRI, including

safety mechanisms, communication styles, and sys-

tem adaptability. In Germany, HRI systems empha-

size precision, compliance, and strict safety protocols,

reﬂecting cultural priorities rooted in structure and

standardization. In contrast, Indian systems prioritize

cost-effectiveness and collaborative human-robot dy-

namics, driven by cultural values of ﬂexibility and in-

clusivity. These insights underscore the importance of

integrating cultural considerations into HRI design to

enhance adaptability and effectiveness in diverse en-

vironments. By embedding cultural awareness during

the early stages of system development, researchers

and practitioners can account for the varying needs,

preferences, and constraints of different societies. For

instance, integrating culturally tailored safety proto-

cols can enhance user trust and acceptance, while

designing adaptable communication systems ensures

that robots interact effectively across linguistic and

social boundaries. Moreover, culturally aware HRI

frameworks can better address ethical concerns, such

as privacy and job displacement, by aligning robot be-

havior with local societal norms. Such considerations

are crucial for fostering meaningful and sustainable

human-robot collaborations in global contexts.

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