Relevant bibliographies by topics / Smart wheelchair navigation

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Smart wheelchair navigation'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Smart wheelchair navigation"

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Mathew, Anitha. "E Wheel: A Smart Wheelchair." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 5497–500. http://dx.doi.org/10.22214/ijraset.2024.61238.

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Abstract: In this project, we propose the development of an innovative smart electric wheelchair tailored to address the needs of individuals with mobility impairments. The primary objective is to enhance their quality of life and promote independence through the integration of cutting-edge technologies. The wheelchair's standout feature lies in its incorporation of advanced control mechanisms, notably head gesture control. This intuitive navigation system allows users to maneuver the wheelchair effortlessly, while also offering joystick controls. Furthermore, the wheelchair integrates a pulse
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Ashwathnarayan, Satish Bhogannahalli, Deekshitha Arsa, Sharath Kumar Yerriyuru Narasimhaiah, Shreyas Anchan, and Giri Prasath. "Performance comparison of indoor navigation and obstacle avoidance methods for low-cost implementation in wheelchairs." International Journal of Reconfigurable and Embedded Systems (IJRES) 14, no. 1 (2025): 100. https://doi.org/10.11591/ijres.v14.i1.pp100-108.

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Wheelchairs are a huge support for the movement of people who have disabilities. The wheelchairs that were traditionally moved using manual effort have given way to powered and smart wheelchairs with various controlling methods. When powered wheelchairs are used indoors, navigation and avoiding obstacles become challenging and tricky for a disabled user. To address these challenges there have been implementations of expensive and high-end systems to make the wheelchair move autonomously but as a result such a wheelchair is not economically viable for many users. Thus, there is a need for an al
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Satish, Bhogannahalli Ashwathnarayan, Deekshitha Arasa, Kumar Yerriyuru Narasimhaiah Sharath, Anchan Shreyas, and Giri Prasath. "Performance comparison of indoor navigation and obstacle avoidance methods for low-cost implementation in wheelchairs." International Journal of Reconfigurable and Embedded Systems (IJRES) 14, no. 1 (2025): 100–108. https://doi.org/10.11591/ijres.v14.i1.pp100-108.

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Wheelchairs are a huge support for the movement of people who have disabilities. The wheelchairs that were traditionally moved using manual effort have given way to powered and smart wheelchairs with various controlling methods. When powered wheelchairs are used indoors, navigation and avoiding obstacles become challenging and tricky for a disabled user. To address these challenges there have been implementations of expensive and high-end systems to make the wheelchair move autonomously but as a result such a wheelchair is not economically viable for many users. Thus, there is a need for an al
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Akkineni, Kalpana, Thodeti Mounika, Malgari Pooja, et al. "Smart Glove or Sign Language and AI-Driven Wheelchair Navigation." MATEC Web of Conferences 392 (2024): 01061. http://dx.doi.org/10.1051/matecconf/202439201061.

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Gesture gloves are a promising solution for individuals who struggle with both mobility and communication. These gloves' sensor technology helps with nonverbal communication as well as mobility, which is especially beneficial for people who have trouble pushing manual wheelchairs[2]. The goal of gesture gloves, a notable development in assistive technology, is to empower people with disabilities by improving mobility and enabling effective communication through natural hand and finger movements[1]. The use of AI-controlled wheelchairs and smart gloves together raises the bar for assistive tech
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J Phaneendra Balaji, Para Keerti, Adnan Bin Salam, Guguloth Sindhuja, and MD Adil Hussain. "Iot-Based Smart Wheelchair for Elderly Healthcare Monitoring." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 05 (2025): 2274–82. https://doi.org/10.47392/irjaeh.2025.0335.

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This paper presents the development and implementation of an Internet of Things (IoT)-enabled smart wheelchair designed to enhance mobility and independence for individuals with disabilities. By integrating advanced assistive technologies and internet connectivity, the system offers a comprehensive solution that addresses key challenges in wheelchair navigation and user autonomy. The smart wheelchair is equipped with a suite of sensors, including ultrasonic and infrared, to perceive its environment, detect obstacles, and provide real-time feedback to the user. These sensors enable the wheelcha
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Dore, Aruna. "Smart Mobility: Voice-Activated Wheelchair for Enhanced Accessibility." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40834.

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This project presents the development of a voice-activated wheelchair designed to enhance accessibility for individuals with limited mobility. Addressing the challenges posed by traditional manual and joystick-controlled wheelchairs, this innovative solution employs readily available and cost-effective components. The system utilizes an Arduino Uno microcontroller as the central processing unit, an L298N motor driver for controlling DC gear motors, and an HC-05 Bluetooth module for wireless communication. A custom-designed interface within a Bluetooth-enabled smartphone application facilitates
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Cui, Jianwei, Yucheng Shang, Siji Yu, and Yuanbo Wang. "Research on Intelligent Wheelchair Multimode Human–Computer Interaction and Assisted Driving Technology." Actuators 13, no. 6 (2024): 230. http://dx.doi.org/10.3390/act13060230.

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The traditional wheelchair focuses on the “human-chair” motor function interaction to ensure the elderly and people with disabilities’ basic travel. For people with visual, hearing, physical disabilities, etc., the current wheelchairs show shortcomings in terms of accessibility and independent travel for this group. Therefore, this paper develops an intelligent wheelchair with multimodal human–computer interaction and autonomous navigation technology. Firstly, it researches the multimodal human–computer interaction technology of occupant gesture recognition, speech recognition, and head postur
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.P.Margale, Ketan, and S. D. .Mangate. "Smart and automatic wheelchair using Arduino Uno." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44224.

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This paper presents a novel approach to wheelchair control using hand gesture recognition, enabling enhanced mobility for individuals with disabilities. The system employs computer vision and sensor-based technologies to interpret predefined hand gestures, translating them into wheelchair movement commands. Using machine learning algorithms, the model ensures accurate gesture recognition with minimal latency. The proposed system enhances accessibility by reducing dependence on physical joysticks or voice commands, making it suitable for users with varying motor abilities. Experimental results
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Bonci, Andrea, Sauro Longhi, Andrea MonteriÙ, and Massimo Vaccarini. "Navigation system for a smart wheelchair." Journal of Zhejiang University SCIENCE 6A, no. 2 (2005): 110–17. http://dx.doi.org/10.1631/jzus.2005.a0110.

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Andrea, Bonci, Longhi Sauro, Monteriù Andrea, and Vaccarini Massimo. "Navigation system for a smart wheelchair." Journal of Zhejiang University-SCIENCE A 6, no. 2 (2005): 110–17. http://dx.doi.org/10.1631/bf02847974.

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Dissertations / Theses on the topic "Smart wheelchair navigation"

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Tang, Robert. "A Semi-autonomous Wheelchair Navigation System." Thesis, University of Canterbury. Mechanical Engineering, 2012. http://hdl.handle.net/10092/6472.

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Many mobility impaired users are unable to operate a powered wheelchair safely, without causing harm to themselves, others, and the environment. Smart wheelchairs that assist or replace user control have been developed to cater for these users, utilising systems and algorithms from autonomous robots. Despite a sustained period of research and development of robotic wheelchairs, there are very few available commercially. This thesis describes work towards developing a navigation system that is aimed at being retro-fitted to powered wheelchairs. The navigation system developed takes a systems e
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Patel, Jayam Umesh. "Gesture Based Navigation and Localization of a Smart Wheelchair using Fiducial Markers." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-theses/449.

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With the rise in aging population, about 6.8 million American residents are depen- dent on mobility devices for their day to day activity. More than 40% of these users have di?culty in moving the mobility device on their own. These numbers serve as a motivation on developing a system than can help in manipulation with simple muscle activity and localize the mobility device in the user's home in case of medical emergencies. This research is aimed at creating a user interface of Elec- tromyographic Sensor, attached to the forearm, incorporated with present smart wheelchairs and a simple localiza
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Devigne, Louise. "Solutions robotiques bas coût pour l’aide à la navigation en fauteuil roulant électrique : vers une contribution dans le champ de la rééducation neurologique." Thesis, Rennes, INSA, 2018. http://www.theses.fr/2018ISAR0024/document.

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Alors que l’utilisation d’un fauteuil roulant permet aux personnes en situation de handicap de compenser une perte de la mobilité, certaines personnes se voient privées de l’utilisation d’un fauteuil roulant électrique. En effet, la présence de troubles cognitifs ou de la perception visuelle altère la capacité à conduire sans danger. Dans ce contexte, l’accès à la mobilité peut être amélioré par l’apport d’aides techniques adaptées permettant de compenser la perte de mobilité dans tous types d’environnements. Alors que les premiers travaux sur les fauteuils roulants intelligents datent du débu
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"Learning human navigational skill for smart wheelchair." 2003. http://library.cuhk.edu.hk/record=b5891618.

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by Hon Nin Chow.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.<br>Includes bibliographical references (leaves 79-84).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Motivation --- p.1<br>Chapter 1.2 --- Organization of the Thesis --- p.3<br>Chapter 2 --- Literature Survey --- p.6<br>Chapter 2.1 --- Learning-by-Demonstration --- p.6<br>Chapter 2.2 --- Neural Networks --- p.7<br>Chapter 2.3 --- Navigation Learning --- p.8<br>Chapter 2.4 --- Localization --- p.9<br>Chapter 2.5 --- Robotic Wheelchair --- p.10<br>Chapter 3 --- Sy
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Book chapters on the topic "Smart wheelchair navigation"

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Freddi, Alessandro, Catia Giaconi, Sabrina Iarlori, Sauro Longhi, Andrea Monteriù, and Daniele Proietti Pagnotta. "Assistive Robot for Mobility Enhancement of Impaired Students for Barrier-Free Education: A Proof of Concept." In Makers at School, Educational Robotics and Innovative Learning Environments. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77040-2_44.

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AbstractSmart wheelchairs are in the category of assistive robots, which interact physically and/or non-physically with people with physical disabilities to extend their autonomy. Smart wheelchairs are assistive robots that enhance mobility, and can be especially useful for improving access to university premises. This paper proposes a smart wheelchair that can be integrated with an academic management system to enable students who have serious leg problems and cannot walk on their own to reach any academic building or room on a university campus autonomously. The proposed smart wheelchair rec
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Razali, Tomari, Rong Zhu, Kobayashi Yoshinori, and Kuno Yoshinori. "Smart Wheelchair Navigation Based on User’s Gaze on Destination." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14831-6_52.

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Markus, Elisha Didam, Teboho Ntsinyi, and Eric Monacelli. "Gesture Recognition-Based Interaction with Smartwatch and Electric Wheelchair for Assistive Mobility and Navigation." In IOT with Smart Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3945-6_9.

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Mohammed, Nawaf, Sulaiman Azzan, Vedanta Jaitoo, Vickneswari Durairajah, and Suresh Gobee. "Smart Wheelchair Navigation Using ROS with Collision Avoidance and 2D Mapping." In IFMBE Proceedings. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56438-3_15.

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Rahman, Muhammad Rameez ur, Piero Simonetto, Anna Polato, Francesco Pasti, Luca Tonin, and Sebastiano Vascon. "OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92591-7_23.

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Wei, Zhixuan, Weidong Chen, Jingchuan Wang, and Huiyu Wang. "Semantic Topological Map-Based Smart Wheelchair Navigation System for Low Throughput Interface." In Intelligent Autonomous Systems 13. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_9.

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Ciabattoni, Lucio, Francesco Ferracuti, Alessandro Freddi, Sabrina Iarlori, Sauro Longhi, and Andrea Monteriù. "Human-in-the-Loop Approach to Safe Navigation of a Smart Wheelchair via Brain Computer Interface." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63107-9_16.

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Abascal, Julio, Borja Bonail, Daniel Cagigas, Nestor Garay, and Luis Gardeazabal. "Trends in Adaptive Interface Design for Smart Wheelchairs." In Handbook of Research on User Interface Design and Evaluation for Mobile Technology. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-871-0.ch042.

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This chapter introduces the main trends in the design of interfaces for smart wheelchairs. It stresses the importance of taking into account their similarity with autonomous mobile robots and the restrictions posed by the special characteristics of the users (people with severe motor and speech restrictions) and the task (indoor assisted navigation). With this background, the main features of the user-wheelchair interface are discussed, justifying the need for the adoption of an adaptive approach. The TetraNauta smart wheelchair interface design is used to illustrate the design of user, contex
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Chen, Ling, Sen Wang, Huosheng Hu, Dongbing Gu, and Ian Dukes. "Voice-directed autonomous navigation of a smart-wheelchair." In Smart Wheelchairs and Brain-Computer Interfaces. Elsevier, 2008. http://dx.doi.org/10.1016/b978-0-12-812892-3.00017-0.

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Noda, Yoshiyuki, Akira Kawaguchi, and Kazuhiko Terashim. "A Mechatronics Vision for Smart Wheelchairs." In Mobile Robots Navigation. InTech, 2010. http://dx.doi.org/10.5772/8996.

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Conference papers on the topic "Smart wheelchair navigation"

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S, Jayasuriya, Dharani Barathi C D, Balaji S, and Sriramalakshmi P. "Smart Wheelchair Navigation: Gesture Control and Obstacle Avoidance." In 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS). IEEE, 2024. https://doi.org/10.1109/icicnis64247.2024.10823349.

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D, Shivamma, Manjula M, S. Bhavani Prasad, Nikunj Vihari Konakalla, Eshwar Reddy M, and Mir Khyrun Ali. "Smart Wheelchair Navigation Using Gesture-Based Control and IoT." In 2025 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE). IEEE, 2025. https://doi.org/10.1109/iitcee64140.2025.10915306.

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Balaji, Sreenidhi, R. S. Varsha Sree, and K. Johny Elma. "Smart Wheelchair based on Gesture Control with Autonomous Navigation." In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). IEEE, 2025. https://doi.org/10.1109/icima64861.2025.11074049.

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Gambhir, Varun, Chaitanya Singh Bisht, Arnav Goe, and Ajay Kumar Gupta. "Microcontroller-Driven Voice-Based Smart Wheelchair Navigation with Neural Networks." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725700.

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Fadhila Rahmaniati, Amila, and Fitri Utaminingrum. "Deep Learning Based Smart Wheelchair Navigation Optimization for Multi-Lighting Conditions." In 2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI). IEEE, 2024. https://doi.org/10.1109/raai64504.2024.10949523.

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Wickramasingha, K. B., G. M. K. B. Karunasena, H. M. K. K. M. B. Herath, and B. G. D. A. Madhusanka. "Eye-Gaze-Based Navigation for Accessible Wheelchair Control in Domestic Environments." In 2025 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2025. https://doi.org/10.1109/scse65633.2025.11031014.

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N, Aswin, Arun A, Manivannan R, and Ganiss Roger L. "IoT-Enabled Smart Wheelchair with Environmental Sensing and Geofencing for Safe and Comfortable Navigation." In 2025 International Conference on Electronics and Renewable Systems (ICEARS). IEEE, 2025. https://doi.org/10.1109/icears64219.2025.10940942.

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Muhammad Alqadri, Ainandafiq, Fitri Utaminingrum, Muhammad Ali Fauzi, Rekyan Regasari Mardi Putri, Corina Karim, and Femiana Gapsari. "Attention Module in YOLO-Based Object Detection Method for Autonomous Smart Wheelchair Room Navigation System." In 2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI). IEEE, 2024. https://doi.org/10.1109/raai64504.2024.10949519.

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Perpetuini, David, Sabrina Iarlori, Daniela Cardone, et al. "Thermal Imaging for Real-Time Monitoring of Stress and Engagement in Autonomous and Manual Smart Wheelchair Navigation." In 2024 E-Health and Bioengineering Conference (EHB). IEEE, 2024. https://doi.org/10.1109/ehb64556.2024.10805677.

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Batayneh, Wafa M., Khaled S. Hatamleh, Amjad A. Nusayr, Rama Alquraan, Aseel Al-Khaleel, and Ahmad Batainah. "Low-Cost Wi-Fi Navigation of Smart Wheelchairs." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86277.

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This paper presents the design and implementation of a low-cost and reliable wireless motion control system for conventional electric wheelchairs. The presented work aims to enhance the mobility of handicapped and elderly wheelchair users by utilizing a mobile application to control the motion of their unattained wheelchairs. The designed system takes into consideration cost, weight, a range of operation, ease of use, and implementation. The conventional electric wheelchair is equipped with a motorized front wheel steering mechanism. In addition, it is equipped with a Wi-Fi module to support r
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