AI ADVANCES IN WHEELCHAIR NAVIGATION AND CONTROL: A COMPREHENSIVE REVIEW

: This paper presents a systematic review of the literature on integrating artificial intelligence (AI) to improve wheelchair navigation and control for people with mobility impairments. The review covers a range of AI-based approaches including computer vision, machine learning, and path planning algorithms. The paper highlights the potential benefits of integrating AI into wheelchair technology, including increased safety, autonomy, and personalized control. The review discusses the limitations and challenges of current wheelchair navigation and control systems, and how AI can address these limitations. The paper identifies common themes and trends in the literature and summarizes the strengths and weaknesses of existing AI-based wheelchair navigation and control systems. Finally, the paper concludes by discussing the potential future directions for research and development of AI-based wheelchair navigation and control systems. This review paper provides a valuable resource for researchers and engineers interested in developing and improving AI-based wheelchair technology.


Introduction
A robotic wheelchair is an advanced form of assistive technology designed to provide mobility and independence to people with severe physical disabilities.Unlike traditional manual wheelchairs, robotic wheelchairs incorporate a range of sensors, actuators, and computing systems that enable them to navigate through indoor and outdoor environments autonomously, and respond to the user's commands and preferences.The technology behind robotic wheelchairs is continually evolving, driven by the increasing demand for more sophisticated, reliable, and user-friendly solutions.The development of robotic wheelchairs holds great promise for enhancing the quality of life of people with mobility impairments, by increasing their access to education, work, and leisure activities, as well as reducing their dependence on caregivers.However, the design and implementation of robotic wheelchairs require a multidisciplinary approach that involves expertise in fields such as robotics, control engineering, human factors, and user-centered design.
Robotic wheelchairs have the potential to revolutionize the way people with mobility impairments interact with their environment.With the help of advanced sensors, algorithms, and user interfaces, these devices can navigate through complex and dynamic environments, avoid obstacles, and adapt to the user's needs and preferences in real-time.Moreover, the integration of robotic technology can also provide users with a greater sense of independence and control, as they can operate the wheelchair with minimal physical effort and interact with their environment in new and innovative ways.Despite the potential benefits of robotic wheelchairs, there are still many challenges that need to be addressed before this technology can become widely available and accessible.Some of these challenges include safety, reliability, usability, and affordability (Sahoo and Choudhury, 2021).Moreover, designing a robotic wheelchair that meets the diverse needs and preferences of different users requires a deep understanding of human factors, ergonomics, and user-centered design principles.
In recent years, there has been a growing interest in the development of robotic wheelchairs, driven by advances in robotics, sensing, and machine learning technologies.Researchers and engineers from various fields have been working together to develop new and innovative solutions to address the challenges associated with robotic wheelchair technology.

Need of wheelchair
The need for wheelchair access to healthcare services is critical, particularly for people with disabilities in low-and middle-income countries (LMICs).According to the World Health Organization (WHO), over 70 million people worldwide require wheelchairs for mobility, and only about 10% of them have access to the wheelchairs they need.This lack of access to appropriate wheelchairs can have a significant impact on their ability to participate in education, employment, and social activities, as well as their overall quality of life (Daza et al., 2022).
Furthermore, the WHO has identified that people with disabilities face multiple barriers to accessing healthcare services, including physical, financial, and attitudinal barriers.These barriers can further exacerbate the challenges faced by people with disabilities in obtaining the necessary healthcare services and contribute to significant health disparities.In response to these challenges, the WHO has developed guidelines for the provision of appropriate wheelchairs in LMICs, which emphasize the importance of providing access to wheelchairs that meet individual needs and preferences.Additionally, the WHO has highlighted the need for comprehensive wheelchair services that address the entire process of wheelchair provision, including assessment, prescription, supply, and maintenance (Sahoo and Choudhury, 2022).
The availability of WHO data on wheelchair provision and disability can provide valuable insights into the needs and challenges faced by people with mobility impairments in different regions and can inform the development of more effective and accessible wheelchair services.By leveraging these data sources, policymakers, healthcare providers, and researchers can better understand the needs and preferences of people with mobility impairments and develop more effective strategies to address the barriers to healthcare access they face.

Role of AI in wheelchair
The role of AI in wheelchair technology is becoming increasingly important in enhancing the mobility and independence of people with mobility impairments.One of the key areas where AI can make a significant impact is in the navigation and obstacle avoidance of wheelchairs.Advanced sensors, algorithms, and machine learning techniques can be employed to enable wheelchairs to navigate through complex and dynamic environments while avoiding obstacles in real-time.This can provide people with mobility impairments with greater independence and access to various locations.Additionally, AI can also be used to personalize the control of the wheelchair to the user's specific needs and preferences.By analyzing data from various sensors, AI algorithms can learn about the user's patterns of movement and adapt the wheelchair's control accordingly (Chandra, 2022).This can improve the user's comfort, safety, and overall experience.Another potential application of AI in wheelchair technology is in the development of predictive maintenance systems.By monitoring various sensors on the wheelchair, AI algorithms can detect potential issues before they become major problems and alert the user or service personnel to take action.This can help prevent breakdowns and increase the overall reliability and lifespan of the wheelchair.
Moreover, AI can also help improve the overall design and functionality of wheelchairs.With the help of AI-powered design tools, engineers can quickly prototype and test new wheelchair designs with optimized ergonomics, weight, and durability.This can lead to the development of more efficient and user-friendly wheelchairs that can better meet the needs of people with mobility impairments.AI can also facilitate the collection and analysis of large amounts of data from wheelchairs in real-world settings.This data can be used to identify usage patterns, detect potential safety issues, and evaluate the overall performance of different wheelchair models (Bourbakis, 2022).By analyzing this data, researchers and manufacturers can develop more effective strategies to improve the design and functionality of wheelchairs.
Lastly, AI can also facilitate the integration of various assistive technologies into wheelchairs, such as robotic arms, speech recognition systems, and environmental control systems.By integrating these technologies into wheelchairs, people with mobility impairments can more easily perform various tasks, communicate with others, and control their environment.Overall, the integration of AI into wheelchair technology has the potential to significantly enhance the mobility and independence of people with mobility impairments, and improve their overall quality of life.

Significance of this Study
The integration of AI into wheelchair navigation and control has significant implications for improving the mobility and independence of people with mobility impairments.Here are some potential significances of a review research paper on integrating AI to improve wheelchair navigation and control: • Enhanced mobility and independence: By improving the navigation and control of wheelchairs, AI can enhance the mobility and independence of people with mobility impairments.This can enable them to participate more fully in various activities, such as education, employment, and social events, and lead a more fulfilling life (Sahoo and Choudhury, 2023).
• Improved safety and comfort: AI-powered navigation and control can help reduce the risk of accidents and injuries associated with wheelchair use.By providing real-time obstacle detection and avoidance, AI can prevent collisions and improve overall safety (Tatano and Revellini, 2023).Additionally, personalized control algorithms can improve user comfort and reduce the risk of repetitive strain injuries.
• Cost-effectiveness: By leveraging AI technologies, wheelchair manufacturers and service providers can develop more cost-effective solutions that meet the needs and preferences of users.This can lead to increased accessibility to advanced wheelchair technologies and services for people with mobility impairments (Ruffing et al., 2023).
• Improved data collection and analysis: The integration of AI into wheelchair technology can facilitate the collection and analysis of large amounts of data from realworld settings.This data can be used to identify usage patterns, detect potential safety issues, and evaluate the overall performance of different wheelchair models (Kambhamettu et al., 2023).By analyzing this data, researchers and manufacturers can develop more effective strategies to improve the design and functionality of wheelchairs.
• Innovation: The integration of AI into wheelchair technology has the potential to drive innovation in the field of mobility and assistive technologies.By leveraging advanced AI algorithms and design tools, researchers and manufacturers can develop more efficient, user-friendly, and effective wheelchair technologies that can better meet the needs and preferences of users (Subramanian et al., 2022).
On integrating AI to improve wheelchair navigation and control have significant implications for improving the quality of life of people with mobility impairments and advancing the field of mobility and assistive technologies.

Objective of the Study
The objectives of this research work on integrating AI to improve wheelchair navigation and control are: • To provide a comprehensive overview of the current state of AI integration in wheelchair navigation and control technology.
• To explore the various AI techniques and algorithms used for obstacle detection, path planning, and personalized control in wheelchair navigation and control.
• To identify the potential benefits and limitations of integrating AI into wheelchair navigation and control, including improved mobility, safety, and cost-effectiveness.
• To analyze the real-world implementation of AI-powered wheelchair technologies and their effectiveness in improving the mobility and independence of people with mobility impairments.
• To examine the ethical and social implications of AI-powered wheelchair technologies, including issues related to privacy, autonomy, and equitable access.
• To provide recommendations for future research and development in the field of AIpowered wheelchair navigation and control, including potential areas of innovation and collaboration.
The objective is to provide a comprehensive understanding of the current and potential role of AI in improving wheelchair navigation and control and to identify opportunities for advancing the field of mobility and assistive technologies.

Literature Review
AI is revolutionizing the field of mobility and assistive technologies, including wheelchair navigation and control.By leveraging advanced algorithms for obstacle detection, path planning, and personalized control, AI can enhance the mobility, safety, and comfort of people with mobility impairments.AI-powered wheelchair technologies can also facilitate the collection and analysis of large amounts of data from real-world settings, providing valuable insights for researchers and manufacturers.The integration of AI into wheelchair technology has significant implications for improving the quality of life of people with mobility impairments and advancing the field of mobility and assistive technologies.
The integration of artificial intelligence (AI) in wheelchair navigation and control technology has advanced significantly in recent years.AI-powered wheelchairs can improve the mobility and independence of users by providing more intuitive and customizable control options.Additionally, AI algorithms can enhance the navigation capabilities of the wheelchair, allowing it to navigate complex environments and avoid obstacles with greater accuracy and safety.A study by Jameel et al. (2022) explored the use of AI algorithms in wheelchair navigation and control.The researchers developed a system that used machine learning to predict the user's intended direction based on their previous movements.The system also incorporated obstacle detection and avoidance capabilities to improve safety.The study demonstrated that the AI-powered wheelchair system could accurately predict the user's intended direction and navigate obstacles in real-time.
Another study by Arshad et al. (2023) investigated the use of deep reinforcement learning (DRL) algorithms in wheelchair navigation.The researchers developed a system that used DRL algorithms to optimize the wheelchair's navigation strategy in real-time.The system was able to navigate complex environments with greater efficiency and accuracy than traditional control methods.AI techniques and algorithms have been used for obstacle detection, path planning, and personalized control in wheelchair navigation and control to improve the mobility and independence of wheelchair users.Here are a few examples as shown in table 1.The integration of AI into wheelchair navigation and control has the potential to provide various benefits for wheelchair users, including improved mobility, safety, and cost-effectiveness.However, there are also limitations to consider.Here are some examples as shown in table 2.
However, there are also limitations to consider when integrating AI into wheelchair navigation and control.For example, the technology may not be accessible or affordable for all users, and there may be privacy concerns related to the collection and use of personal data.The integration of AI into wheelchair navigation and control has the potential to provide significant benefits for users, but it is important to consider the potential limitations as well.The implementation of AI-powered wheelchair technologies has shown promising results in improving the mobility and independence of people with mobility impairments.Here are some examples of real-world implementations and their effectiveness as shown in table 3.
The implementation of AI-powered wheelchair technologies has shown promising results in improving the mobility and independence of people with mobility impairments.However, there are still challenges to overcome, such as the accessibility and affordability of the technology, as well as the need for further research and development.
The implementation of AI-powered wheelchair technologies raises important ethical and social implications that need to be considered.Here are some of the key issues as shown in table 4. The ethical and social implications of AI-powered wheelchair technologies need to be carefully considered to ensure that these technologies are used in ways that are respectful of users' privacy, autonomy, and equitable access.

Current state of AI integration in wheelchair navigation and control
The current state of AI integration in wheelchair navigation and control technology is advancing rapidly.AI is being used to enhance the mobility and independence of people with mobility impairments in several ways.One of the primary uses of AI in wheelchair navigation and control technology is in obstacle detection and avoidance.Machine learning algorithms, such as deep neural networks, are being utilized to recognize and classify various obstacles in real-time.This enables the wheelchair to navigate safely around them, reducing the risk of collisions.They demonstrated that an AI-powered wheelchair system improved the mobility of users with severe motor impairments.The system used machine learning algorithms to predict the user's intended movements and controls the wheelchair (Sun et al., 2023).
2 Safety Guo et al.
They demonstrated that an AI-powered wheelchair system improved safety for users with cognitive impairments.(Guo et al., 2023). 3

Castro and New
They demonstrated that an AI-powered wheelchair system was more cost-effective than traditional control methods.The system used reinforcement learning algorithms to optimize the wheelchair's control parameters, resulting in reduced energy consumption and longer battery life (Castro and New, 2016).

Hemmati and Rahmani
They implemented an AI-powered wheelchair system that used machine learning algorithms to detect and avoid obstacles.The system was tested in real-world environments with users with motor impairments, and it was found to improve navigation performance and reduce the risk of collisions (Hemmati and Rahmani, 2022).

Subhashini and Krishnaveni
They implemented an AI-powered wheelchair system that used deep reinforcement learning algorithms to optimize personalized control options for users with varying degrees of motor impairments.The system was found to improve the accuracy and efficiency of navigation, and it was well-received by users (Subhashini and Krishnaveni, 2021).

Ghosh
They implemented an AI-powered wheelchair system that used computer vision algorithms to detect and prevent unsafe behaviors, such as driving too fast or entering restricted areas.The system was tested with users with cognitive impairments and was found to improve safety and reduce the need for human assistance (Ghosh, 2021).
Another important use of AI in wheelchair technology is in personalized control options.Deep reinforcement learning algorithms are being employed to optimize the control options for individual users.This takes into account their unique motor impairments and preferences, allowing them to control their wheelchair more efficiently and accurately.AI is also being used to improve safety features in wheelchair navigation and control technology.
Computer vision algorithms are being utilized to detect and prevent unsafe behaviors, such as driving too fast or entering restricted areas.This improves safety and reduces the need for human assistance (al-Qayasi et al., 2018).Despite these promising uses of AI in wheelchair technology, there are potential limitations and challenges.Issues related to privacy, autonomy, and equitable access must be carefully considered to ensure that these technologies are used in ways that respect users' rights and needs.Additionally, there may be limitations to the accessibility and affordability of the technology, and further research and development is needed to fully realize the potential benefits of AI in wheelchair navigation and control technology.
One key area of AI integration in wheelchair navigation and control technology is path planning.Machine learning algorithms are being used to develop more efficient and personalized paths for wheelchair users.This involves considering the user's unique physical abilities and preferences, as well as the environment in which they will be navigating.By optimizing the path, AI can help users conserve their energy and reduce fatigue, while also improving safety and reducing the risk of collisions (Sahoo and Goswami, 2024).Another promising area of AI integration is the use of wearable sensors to monitor the user's health and well-being.For example, sensors can be used to detect changes in heart rate, blood pressure, or skin temperature, which can signal the onset of a medical emergency.Machine learning algorithms can be used to analyze this data and alert caregivers or emergency responders when necessary (Tonin et al., 2021).This can improve safety and provide greater peace of mind for wheelchair users and their loved ones.
However, there are also potential challenges and limitations to the integration of AI in wheelchair navigation and control technology.One challenge is the complexity of the technology and the need for specialized training and expertise to operate it effectively.This can limit its accessibility and affordability for some users, particularly those in low-income or resource-limited settings (Yenugula et al., 2024).Another challenge is the potential for unintended consequences, such as the reinforcement of existing biases or discrimination.For example, if AI algorithms are trained on data that reflects existing social biases, they may inadvertently perpetuate those biases in their decision-making.This highlights the need for careful consideration of ethical and social implications in the development and deployment of AI-powered wheelchair technologies (Yenugula et al., 2023).AI-powered wheelchair technologies may be designed to assist users in navigating their environment, but it is important to ensure that users still have control over their own actions and decisions.They discusses the importance of maintaining user autonomy and the potential risks of overreliance on AI (Parasuraman and Riley, 1997).
3 Equitable access Zdravkova AI-powered wheelchair technologies have the potential to improve mobility and independence for people with mobility impairments, but there is a risk that these technologies may only be available to those who can afford them.It is important to consider issues of equitable access and ensure that these technologies are available to all who could benefit from them.They discuss the need for affordable and accessible AI-powered assistive technologies (Zdravkova, 2022) In addition to the potential benefits and challenges mentioned earlier, the current state of AI integration in wheelchair navigation and control technology also includes ongoing research and development to enhance the capabilities of these systems.For example, researchers are exploring the use of natural language processing (NLP) algorithms to allow users to control their wheelchairs using voice commands.This could provide a more intuitive and user-friendly interface for individuals who have difficulty with manual controls (McCoy et al., 2013).There is also ongoing work to develop AI-powered exoskeletons and other mobility devices that can provide additional support and assistance for individuals with mobility impairments.These devices can incorporate sensors and machine learning algorithms to adapt to the user's movements and provide additional support where needed.This has the potential to significantly improve the mobility and independence of individuals with more severe mobility impairments.
Finally, there is growing interest in the use of AI-powered wheelchair technologies in lowincome and resource-limited settings.This includes developing more affordable and accessible solutions that can be deployed in areas where traditional wheelchair technologies may be difficult to obtain or maintain.This has the potential to significantly improve access to mobility and independence for individuals in these settings (Rajaprakash et al., 2019).Overall, the current state of AI integration in wheelchair navigation and control technology is dynamic and rapidly evolving.While there are still challenges and limitations to overcome, the potential benefits are significant and the ongoing research and development in this field are promising.With continued innovation and collaboration, AI-powered wheelchair technologies have the potential to transform the lives of millions of individuals with mobility impairments around the world.

AI techniques and algorithms for obstacle detection and path planning
As technology continues to advance, there has been a growing interest in integrating artificial intelligence (AI) into wheelchair navigation and control systems.By leveraging the power of AI, it is possible to improve the independence, safety, and mobility of people with mobility impairments.One of the key areas where AI can make a significant impact is in obstacle detection, path planning, and personalized control.These are critical components of wheelchair navigation and control, and by applying various AI techniques and algorithms, researchers and developers are able to create more sophisticated systems that can better adapt to the needs and preferences of users.

Various AI techniques and algorithms used for obstacle detection
AI techniques and algorithms used for obstacle detection in wheelchair navigation include computer vision techniques, such as object detection and segmentation, and sensor-based approaches, such as LiDAR and ultrasonic sensors.These techniques use machine learning and signal processing algorithms to detect and localize obstacles in the environment, enabling the wheelchair to navigate safely as shown in table 5.
It is important to note that this is not an exhaustive list and that there may be other AI techniques and algorithms used for these applications in wheelchair navigation and control.Additionally, different researchers and developers may use a combination of these techniques and algorithms to achieve their desired outcomes.

Various AI techniques and algorithms used for path planning
AI techniques and algorithms used for path planning in wheelchair navigation include A* search, Dijkstra's algorithm, Rapidly Exploring Random Trees (RRT), and potential fields.These techniques use machine learning and optimization algorithms to generate safe and efficient paths for the wheelchair to navigate through complex environments as shown in table 6.These techniques and algorithms can be combined and customized to meet the specific needs of individual wheelchair users.They can help improve safety, efficiency, and comfort in wheelchair navigation and control, while also promoting greater independence and autonomy for users with mobility impairments.Uses a statistical approach to estimate the location and movement of the wheelchair, which can be used to plan the path.

Decision Trees Path Planning
Uses a hierarchical structure to make decisions about the best path to take, based on the user's preferences and the environment.

Particle Swarm Optimization Path Planning
Uses a swarm of particles to optimize the path, based on the user's requirements and the environment.

Path Planning
Uses trial and error to learn the best path for a wheelchair user, based on their preferences and physical abilities.

Ant Colony Optimization Path Planning
Uses a swarm of virtual ants to find the shortest path between two points, based on pheromone trails and heuristics.

Various AI techniques and algorithms used for personalized control
AI techniques and algorithms used for personalized control in wheelchair navigation and control include reinforcement learning, supervised learning, unsupervised learning, and deep learning.These techniques enable the wheelchair to make personalized decisions based on user preferences and behavior patterns, allowing for more intuitive and efficient navigation as shown in table 7.These techniques and algorithms, along with the ones previously mentioned, demonstrate the versatility and potential of AI in wheelchair navigation and control.By leveraging the power of AI, researchers and developers are able to create more advanced and sophisticated systems that can better adapt to the needs and preferences of users with mobility impairments, ultimately leading to improved quality of life and increased independence.Uses neural networks to learn the user's preferences and optimize the wheelchair's controls for their needs.

3
Hidden Markov Models

Personalized Control
Uses probabilistic modeling to predict the user's next move and adjust the wheelchair controls accordingly.

Gaussian Process Regression
Personalized Control Uses probabilistic modeling to learn the user's preferences and optimize the wheelchair controls based on their individual needs and comfort.

Q-Learning Personalized Control
Uses a reinforcement learning approach to learn the user's preferences and adjust the wheelchair controls based on their individual needs and comfort.

Personalized Control
Uses a statistical technique to analyze the wheelchair user's movements and preferences, and adjust the wheelchair controls accordingly.

Personalized Control
Uses a trial-and-error approach to learn the user's preferences and adjust the wheelchair controls accordingly.

Fuzzy Logic Personalized Control
Uses a mathematical approach to handle uncertainty and imprecision, and adjust the wheelchair controls based on the user's preferences and comfort.

Potential benefits and limitations of integrating AI into wheelchair
Integrating AI into wheelchair navigation and control can offer numerous benefits, including improved mobility, increased safety, cost-effectiveness, customization, and increased accessibility.AI can enable wheelchairs to navigate in real-time, detect obstacles, and avoid collisions, giving users greater independence and control.However, integrating AI into wheelchair technology also has limitations, including technical challenges, cost, user acceptance, maintenance, and ethical considerations.Addressing these limitations is crucial for ensuring that AI-powered wheelchair technologies are developed and deployed in an ethical, inclusive, and effective manner that promotes the autonomy, safety, and well-being of users with disabilities.

Benefits of integrating AI into wheelchair navigation and control
• Improved Mobility: AI-powered wheelchair navigation and control systems can improve mobility for users with limited physical abilities.AI can help the wheelchair to navigate in real-time and avoid obstacles, which can enable users to move more freely and independently (Mathur et al., 2021).
• Increased Safety: AI-powered wheelchair navigation and control systems can improve the safety of the user by detecting potential hazards in the environment and avoiding collisions with other objects or people.This can reduce the risk of accidents and injuries, giving users greater peace of mind (Singh et al., 2018).
• Cost-Effective: AI-powered wheelchair navigation and control systems have the potential to be more cost-effective than traditional wheelchair technologies.By integrating sensors and machine learning algorithms, users can control their wheelchair more effectively and with less assistance from caregivers, potentially reducing the need for additional support and resources (Wang et al., 2011).
• Customization: AI-powered wheelchair navigation and control systems can be customized to meet the specific needs of individual users.This means that users can have more control over their mobility and can tailor their wheelchair's navigation and control systems to meet their unique physical and cognitive abilities (Niijima et al., 2019) .
• Increased Accessibility: AI-powered wheelchair navigation and control systems can increase accessibility for users with physical disabilities.With the ability to navigate through different terrains and environments, users can have greater access to public spaces, improving their quality of life (Goswami et al., 2020).

Limitations of integrating AI into wheelchair navigation and control
• Technical Challenges: The integration of AI into wheelchair navigation and control systems requires advanced technologies such as sensors, machine learning algorithms, and computer vision.This can be technically challenging and may require significant investment in research and development (Desai et al., 2017).
• Cost: While AI-powered wheelchair navigation and control systems have the potential to be cost-effective in the long term, the initial investment required to develop and implement these technologies can be high, making them inaccessible to some users and healthcare facilities (Al-Qayasi et al., 2018).
• User Acceptance: Some users may be hesitant to adopt AI-powered wheelchair navigation and control systems due to concerns about reliability, privacy, and autonomy.This can limit the adoption of these technologies, particularly among older adults and those with cognitive impairments (Dey et al., 2019).
• Maintenance: AI-powered wheelchair navigation and control systems require regular maintenance and updates to ensure their continued functionality.This can be costly and time-consuming, requiring specialized expertise and resources (McLean et al., 2021).
• Ethical Considerations: The use of AI-powered wheelchair navigation and control systems raises ethical considerations, particularly around issues of privacy and autonomy.As these technologies become more advanced, it will be important to address these issues to ensure that users are empowered and protected (Ouallane et al., 2022).

Ethical and social implications of AI-powered wheelchair
The development and deployment of AI-powered wheelchair technologies can have significant ethical and social implications.Here are some of the key considerations: i.
Autonomy and Control: AI-powered wheelchair technologies have the potential to enhance the autonomy and control of users with disabilities.However, it is essential to ensure that users have full control over their wheelchair and that the technology does not take over or restrict the user's freedom of movement (Lott et al., 2022). ii.
Privacy: AI-powered wheelchair technologies rely on data collected from users, including their movements, behaviors, and preferences.It is essential to protect the privacy of users and ensure that their data is not misused or shared without their consent (Fosch-Villaronga and Drukarch, 2022). iii.
Bias and Discrimination: AI-powered wheelchair technologies may be subject to bias and discrimination, particularly if they are trained on datasets that are not representative of the user population.It is essential to ensure that these technologies are developed and deployed in an ethical and inclusive manner to avoid perpetuating existing inequalities (Bolturk et al., 2021).
iv. Safety: AI-powered wheelchair technologies must be designed and tested to ensure that they are safe and reliable.The potential for accidents or malfunctions can have significant consequences for users and their caregivers (Bohr and Memarzadeh, 2022). v.
Stigma: AI-powered wheelchair technologies may perpetuate the stigma associated with disabilities, particularly if they are perceived as a "last resort" or "inferior" to traditional mobility aids.It is essential to promote the positive aspects of these technologies and ensure that users are not stigmatized or marginalized (Ienca and Ignatiadis, 2022).
vi. Accessibility: AI-powered wheelchair technologies have the potential to increase accessibility for users with disabilities.However, it is essential to ensure that these technologies are accessible and affordable for all users, regardless of their socioeconomic status or geographical location (Kane et al., 2022). vii.
Human Interaction: AI-powered wheelchair technologies may reduce the need for human interaction and support, which can have both positive and negative implications.It is essential to strike a balance between the benefits of increased autonomy and control and the need for social interaction and support (Bourahmoune and Amagasa, 2019).

viii.
Responsibility and Liability: AI-powered wheelchair technologies raise questions about responsibility and liability, particularly in the event of accidents or malfunctions.
It is essential to clarify the roles and responsibilities of users, caregivers, and manufacturers to ensure that users are protected and that accountability is clear (Uma, 2023).

Conclusion
The integration of AI into wheelchair navigation and control has the potential to revolutionize the lives of people with disabilities.This research paper reviewed current technologies and future directions in AI-powered wheelchairs, highlighting the benefits and limitations of integrating AI into wheelchair technology.The current technologies are already making strides in this area, offering increased safety, efficiency, and personalization.However, there are also limitations and challenges to be addressed, including ethical considerations and technical issues.As AI technology continues to advance, there is a promising future for further improving wheelchair navigation and control with more advanced and accessible AI-powered solutions.
This research paper provides valuable insights into the current state of AI-powered wheelchairs and the future directions in this field.It highlights the importance of addressing the challenges and limitations of AI-powered wheelchair technology to ensure that it is developed and deployed in an ethical, inclusive, and effective manner.The future of integrating AI into wheelchair technology looks promising, with advancements in AI technology enabling new capabilities and opportunities for wheelchair navigation and control.Further research and development in this area have the potential to bring about significant improvements in mobility and inclusion for people with disabilities.

Practical Implication
The practical implications of this research paper are significant for researchers, engineers, and healthcare professionals working in the field of assistive technology.The integration of AI into wheelchair navigation and control has the potential to significantly improve the mobility, safety, and autonomy of people with disabilities.The review of current technologies and future directions in this field provides valuable insights for designing and developing AI-powered wheelchair technology that is accessible, reliable, and effective.
Practically, this research paper highlights the need for interdisciplinary collaboration and user-centered design when developing AI-powered wheelchair technology.It also emphasizes the importance of addressing technical challenges such as reliable obstacle detection, computational efficiency, and real-time control.Furthermore, the ethical and social implications of AI-powered wheelchair technology should be considered to ensure equitable access, privacy, and autonomy for users.
The practical implications of this research paper extend beyond the field of assistive technology and have implications for society at large.By improving the mobility and inclusion of people with disabilities, AI-powered wheelchair technology has the potential to promote greater social equity and diversity.This research paper encourages further research and development in this area to ensure that the benefits of AI-powered wheelchair technology are accessible to all.

Limitation
There are several limitations to this research paper that should be considered.Firstly, the review of current technologies and future directions in AI-powered wheelchair technology may not be exhaustive, as the field is rapidly advancing.Secondly, the limitations of AI-powered wheelchair technology, such as the computational requirements, technical challenges, and ethical considerations, may not have been covered in sufficient depth.Additionally, the research paper may have limited applicability in regions with limited access to technology or resources.
Furthermore, the research paper primarily focuses on the benefits of AI-powered wheelchair technology, with limited emphasis on the potential drawbacks and challenges.While the benefits of AI-powered wheelchair technology are significant, they must be balanced with considerations of accessibility, affordability, and user acceptance.
Finally, this research paper is a review and synthesis of existing literature and does not include any primary research.Future studies should consider primary research to validate the findings of this research paper and address any gaps or limitations.
Overall, while this research paper provides valuable insights into the current state and future directions of AI-powered wheelchair technology, the limitations of the research must be considered in interpreting the findings and drawing practical implications.

Future Scope
The future scope of research on AI-powered wheelchair technology is vast and promising.The integration of AI into wheelchair navigation and control has the potential to revolutionize the field of assistive technology and improve the lives of people with disabilities.The review of current technologies and future directions in this research paper has identified several areas where further research and development are needed to realize the full potential of AI-powered wheelchair technology.
One area for future research is improving the reliability and accuracy of obstacle detection algorithms, which can enhance safety and autonomy for users.Additionally, there is a need for research on developing AI-powered wheelchair technology that is more accessible and affordable, particularly in regions with limited resources or infrastructure.
Another area of future research is exploring the potential of AI-powered wheelchair technology for telemedicine and remote healthcare.This could involve integrating sensors and AI algorithms that can monitor the user's health and alert healthcare professionals in case of emergencies.
Finally, the ethical and social implications of AI-powered wheelchair technology should be further explored.This includes ensuring that AI-powered wheelchair technology is developed and deployed in an equitable and inclusive manner, taking into account the needs and preferences of diverse user groups.Overall, the future scope of research on AI-powered wheelchair technology is promising and offers significant potential for advancing the field of assistive technology and improving the lives of people with disabilities.

Table 3 .
Personalized control

Table 4 .
Ethical and social implications

Table 5 .
AI techniques and algorithms for obstacle detection

Table 6 .
AI techniques and algorithms for path planning

Table 7 .
AI techniques and algorithms for personalized control