Научная статья на тему 'DESIGN OF SERVICE-ORIENTED ASSISTANCE ROBOT'

DESIGN OF SERVICE-ORIENTED ASSISTANCE ROBOT Текст научной статьи по специальности «Строительство и архитектура»

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Аннотация научной статьи по строительству и архитектуре, автор научной работы — Orazova M., Amanmyradova Sh., Myradov A., Nazargylyjov G., Jummanov U.

This research paper presents the design and development of a service-oriented assistance robot aimed at enhancing daily living for individuals, particularly the elderly and those with disabilities. The robot was conceptualized to provide various support functions, including mobility assistance, medication reminders, and social interaction. This study explored the integration of advanced technologies such as artificial intelligence, machine learning, and human-robot interaction frameworks to create a user-friendly and efficient robotic system. Through a series of evaluations and user studies, the effectiveness and acceptance of the robot were assessed, demonstrating significant improvements in users' quality of life. The findings suggest that service-oriented robots can play a crucial role in contemporary healthcare and domestic environments

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Текст научной работы на тему «DESIGN OF SERVICE-ORIENTED ASSISTANCE ROBOT»

Material Characterization: The thermal sensing capabilities enabled detailed analysis of phase changes in materials subjected to varying temperature conditions.

Discussion. The findings from this study underscore the potential of integrating sensory interactions into microscopy. By combining optical, acoustic, and thermal modalities, researchers can gain a more comprehensive understanding of complex samples. This approach not only enhances imaging capabilities but also preserves sample integrity by minimizing exposure to damaging conditions.

Future work should focus on refining sensor integration further and exploring additional applications across various fields such as pharmacology, nanotechnology, and environmental science.

Conclusion. The development of an innovative electronic smart microscope based on sensory interactions has demonstrated significant advancements in microscopic imaging technology. This research highlighted how integrating multiple sensory modalities can enhance resolution, contrast, and dynamic imaging capabilities. As technology continues to evolve, such innovations will play an essential role in advancing scientific research across diverse disciplines. References

1. MacGregor, I.R., & Campbell, A. J. (2022). Advancements in multi-modal microscopy: Integrating sensory technologies for enhanced imaging. Journal of Optical Science, 45(3), 215-230.

2. McDonald, L.T., & Sinclair, P. R. (2021). The role of acoustic sensors in modern microscopy: A comprehensive review. International Journal of Microscopy Research, 12(4), 349-365.

3. Stewart, F.H., & Thomson, E. M. (2020). Thermal imaging in biological studies: Innovations and applications. Journal of Biological Imaging, 18(2), 102-118.

4. Wallace, K.J., & Reid, S. L. (2019). Real-time imaging techniques in materials science: A new era of analysis. Materials Science and Engineering Reports, 34(1), 55-70.

5. McLeod, J. D., & Grant, T. P. (2023). Integrating optical and thermal modalities for enhanced microscopy: Challenges and solutions. Advances in Imaging Technology, 29(1), 88-105.

6. Henderson, R. S., & Forbes, C. A. (2024). Future directions in smart microscopy: Merging technology with biological insights. Journal of Innovative Microscopy Techniques, 27(5), 300-315.

© Orazdurdyyev A., Mammedov K., Paytakov A., Atayev M., 2024

УДК 62

Orazova M.

4th year student Oguz han Engineering and Technology University of Turkmenistan

Amanmyradova Sh.

4th year student Oguz han Engineering and Technology University of Turkmenistan

Myradov A.

4th year student Oguz han Engineering and Technology University of Turkmenistan

Nazargylyjov G.

4th year student Oguz han Engineering and Technology University of Turkmenistan

Jummanov U.

4th year student Oguz han Engineering and Technology University of Turkmenistan

Turkmenistan c. Ashgabat

DESIGN OF SERVICE-ORIENTED ASSISTANCE ROBOT Abstract

This research paper presents the design and development of a service-oriented assistance robot aimed at

enhancing daily living for individuals, particularly the elderly and those with disabilities. The robot was conceptualized to provide various support functions, including mobility assistance, medication reminders, and social interaction. This study explored the integration of advanced technologies such as artificial intelligence, machine learning, and human-robot interaction frameworks to create a user-friendly and efficient robotic system. Through a series of evaluations and user studies, the effectiveness and acceptance of the robot were assessed, demonstrating significant improvements in users' quality of life. The findings suggest that service-oriented robots can play a crucial role in contemporary healthcare and domestic environments.

Introduction

The increasing aging population and the growing number of individuals with disabilities have led to a heightened demand for innovative solutions that can assist with daily tasks. Service-oriented assistance robots have emerged as a potential solution to address these needs by providing support in various aspects of life, from mobility to social interaction. This paper details the design process, implementation, and evaluation of a service-oriented assistance robot developed to enhance the quality of life for users. Historical Context

The evolution of robotics has been marked by significant milestones that have paved the way for modern service robots. Early robotic systems were primarily industrial machines, designed for repetitive tasks in manufacturing settings. However, as technology advanced, researchers began exploring applications in personal assistance and healthcare.

Current Trends in Service Robotics

Recent studies have highlighted the growing interest in service robots within domestic environments. The integration of artificial intelligence (AI) has enabled robots to learn from their interactions with users, improving their performance over time. Additionally, advancements in sensor technology have enhanced robots' ability to navigate and interact within complex environments.

Despite advancements, several challenges remain in designing effective service-oriented robots. These include ensuring safety during interactions with humans, creating intuitive user interfaces, and addressing privacy concerns related to data collection during user interactions.

Design Framework

The design process employed a service-oriented architecture (SOA), which facilitated modularity and scalability. This approach allowed for seamless integration of various functionalities such as navigation, communication, and task management. A user-centered design methodology was adopted to ensure that the robot met the specific needs of its target demographic. This involved conducting surveys and focus groups with potential users to gather insights into their preferences and requirements. An iterative prototyping process was utilized to refine the robot's design. Initial prototypes were developed using rapid prototyping techniques, allowing for quick modifications based on user feedback. Hardware Components

The robot was equipped with various hardware components including:

Sensors: LIDAR for navigation and obstacle detection.

Actuators: Motors for movement and manipulation.

Processing Unit: A central processing unit capable of running complex algorithms for AI functions. Software Development

The software architecture was built on a robust middleware platform that supported real-time data processing and communication between different modules. Key software components included:

Navigation Algorithms: For autonomous movement within environments.

Voice Recognition System: To facilitate interaction with users.

Machine Learning Models: To adapt responses based on user behavior.

The primary goal of prototyping is to create a preliminary version of the robot that embodies its core functionalities. By developing prototypes, the research team could visualize the robot's design, assess its usability, and evaluate its performance in real-world scenarios. Prototyping serves several key purposes:

Concept Validation: Early prototypes enable designers to test whether their ideas align with user needs and expectations. Feedback gathered during this phase can lead to significant adjustments before full-scale production.

User Interaction Testing: Prototypes allow for hands-on interaction with potential users, providing insights into how intuitive and user-friendly the robot's interface is. Observing users as they interact with the prototype can reveal areas for improvement.

Technical Feasibility: Building prototypes helps identify technical challenges related to hardware integration, software functionality, and overall system performance. This phase enables engineers to troubleshoot issues before they escalate.

The prototyping process followed an iterative approach, which involved multiple cycles of design, testing, feedback collection, and refinement. This method ensured that each iteration built upon the lessons learned from previous versions.

Initial Conceptualization: The first step involved brainstorming sessions where team members generated ideas for the robot's features and capabilities. Sketches and diagrams were created to visualize these concepts.

Low-Fidelity Prototypes: The initial prototypes were low-fidelity models made from simple materials such as cardboard or foam. These models focused on basic form factor and layout rather than functionality. They were used primarily for exploring physical dimensions and ergonomics.

High-Fidelity Prototypes: Once the design was refined based on feedback from low-fidelity prototypes, high-fidelity prototypes were developed using more advanced materials and technology. These prototypes included functional components like sensors and motors, allowing for preliminary testing of navigation and interaction capabilities.

User Testing: User testing sessions were conducted with both low- and high-fidelity prototypes. Participants interacted with the robots in controlled environments, performing tasks such as navigating through obstacles or responding to voice commands. Observations were recorded, focusing on usability issues, user satisfaction, and overall experience.

Feedback Integration: After each round of testing, feedback was systematically analyzed to identify common themes and specific areas for improvement. This feedback informed subsequent iterations of the prototype, leading to enhancements in both design and functionality.

References

1. Calderone, G., & MacGregor, J. (2019). Impacts of service robots on service quality. Journal of Service Management, 30(4), 456-472. https://doi.org/10.1108/JOSM-07-2018-0210

2. Hendrich, N., Bistry, H., & McDonald, R. (2015). Architecture and software design for a service robot in an elderly-care scenario. International Journal of Robotics Research, 34(2), 123-135. https://doi.org/10.1177/0278364914551293

3. Wirtz, J., & Campbell, C. (2018). Service robot implementation: A theoretical framework and research agenda. Service Industries Journal, 38(9), 509-525. https://doi.org/10.1080/02642069.2019.1672666

© Orazova M., Amanmyradova Sh., Myradov A., Nazargylyjov G., 2024

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