A review of assistive spatial orientation and navigation technologies for the visually impaired


The overall objective of this work is to review the assistive technologies that have been proposed by researchers in recent years to address the limitations in user mobility posed by visual impairment. This work presents an “umbrella review.” Visually impaired people often want more than just information about their location and often need to relate their current location to the features existing in the surrounding environment. Extensive research has been dedicated into building assistive systems. Assistive systems for human navigation, in general, aim to allow their users to safely and efficiently navigate in unfamiliar environments by dynamically planning the path based on the user’s location, respecting the constraints posed by their special needs. Modern mobile assistive technologies are becoming more discrete and include a wide range of mobile computerized devices, including ubiquitous technologies such as mobile phones. Technology can be used to determine the user’s location, his relation to the surroundings (context), generate navigation instructions and deliver all this information to the blind user.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

Change history

  • 12 October 2017

    The fourth author name was missed in the original publication. The correct list of authors should read as ���Hugo Fernandes, Paulo Costa, Vitor Filipe, Hugo Paredes, Jo��o Barroso���. It has been corrected in this erratum. The original article has been updated.

  • 12 October 2017

    The fourth author name was missed in the original publication. The correct list of authors should read as ���Hugo Fernandes, Paulo Costa, Vitor Filipe, Hugo Paredes, Jo��o Barroso���. It has been corrected in this erratum. The original article has been updated.


  1. 1.

    WHO: Visual impairment and blindness, Fact Sheet nº282. http://www.who.int/mediacentre/factsheets/fs282/en/ (2014). Accessed 16th March 2015

  2. 2.

    Hakobyan, L., Lumsden, J., O’Sullivan, D., Bartlett, H.: Mobile assistive technologies for the visually impaired. Surv. Ophthalmol. 58(6), 513–528 (2013). doi:10.1016/j.survophthal.2012.10.004

    Article  Google Scholar 

  3. 3.

    WHO: International Statistical Classification of Diseases and Related Health Problems (ICD-10), vol. 2. WHO, Geneva (2010)

    Google Scholar 

  4. 4.

    Foley, A., Ferri, B.A.: Technology for people, not disabilities: ensuring access and inclusion. J. Res. Spec. Educ. Needs 12(4), 192–200 (2012). doi:10.1111/j.1471-3802.2011.01230.x

    Article  Google Scholar 

  5. 5.

    Mountain, G.: Using the evidence to develop quality assistive technology services. J. Integr. Care 12(1), 19–26 (2004). doi:10.1108/14769018200400005

    Article  Google Scholar 

  6. 6.

    Scherer, M. J.: Living in the state of stuck: How assistive technology impacts the lives of people with disabilities, 4th edn. Cambridge, MA: Brookline Books (2005)

  7. 7.

    Takizawa, H., Yamaguchi, S., Aoyagi, M., Ezaki, N., Mizuno, S.: Kinect cane: object recognition aids for the visually impaired. In: Paja, W.A., Wilamowski, B.M. (eds.) 2013 6th International Conference on Human System Interactions. Conference on Human System Interaction, pp. 473–478 (2013)

  8. 8.

    (BRE) BRE.: Research findings No 4: helping people with sight loss in their homes: housing-related assistive technology. http://www.pocklington-trust.org.uk/researchandknowledge/publications/op3 (2003). Accessed 10th March 2015

  9. 9.

    Montello, D.R.: Cognitive research in giscience: recent achievements and future prospects. Geogr. Compass 3(5), 1824–1840 (2009). doi:10.1111/j.1749-8198.2009.00273.x

    Article  Google Scholar 

  10. 10.

    Jacobson, R.D.: Cognitive mapping without sight: four preliminary studies of spatial learning. J. Environ. Psychol. 18(3), 289–305 (1998). doi:10.1006/jevp.1998.0098

    Article  Google Scholar 

  11. 11.

    Jacquet, C., Bellik, Y., Bourda, Y.: Electronic locomotion aids for the blind: towards more assistive systems. In: Ichalkaranje, N., Ichalkaranje, A., Jain, L.C. (eds.) Intelligent Paradigms for Assistive and Preventive Healthcare, vol. 19. Studies in Computational Intelligence, pp. 133–163. Springer, Berlin (2006). doi:10.1007/11418337_5

  12. 12.

    Passini, R., Proulx, G., Rainville, C.: The spatio-cognitive abilities of the visually impaired population. Environ. Behav. 22(1), 91–118 (1990). doi:10.1177/0013916590221005

    Article  Google Scholar 

  13. 13.

    Song, J.-W., Yang, S.-H.: Touch your way: haptic sight for visually impaired people to walk with independence. In: Proceeding of the CHI '10 Extended Abstracts on Human Factors in Computing Systems, pp. 3343–3348. ACM, New York, NY (2010)

  14. 14.

    Manduchi, R., Kurniawan, S., Bagherinia, H.: Blind guidance using mobile computer vision: a usability study. Paper Presented at the Proceedings of the 12th International ACM SIGACCESS Conference on Computers and Accessibility, Orlando, Florida, USA (2010)

  15. 15.

    Fallah, N., Apostolopoulos, I., Bekris, K., Folmer, E.: Indoor human navigation systems: a survey. Interact. Comput. 25(1), 21–33 (2013). doi:10.1093/iwc/iws010

    Article  Google Scholar 

  16. 16.

    D’Atri, E., Medaglia, C.M., Serbanati, A., Ceipidor, U.B.: A system to aid blind people in the mobility: a usability test and its results. In: Second International Conference on Systems, 2007. ICONS ‘07. 22–28 April 2007, pp. 35–35. (2007). doi:10.1109/ICONS.2007.7

  17. 17.

    Kulyukin, V., Gharpure, C., Nicholson, J., Osborne, G.: Robot-assisted wayfinding for the visually impaired in structured indoor environments. Auton. Robot. 21(1), 29–41 (2006). doi:10.1007/s10514-006-7223-8

    Article  Google Scholar 

  18. 18.

    Willis, S., Helal, S.: RFID information grid for blind navigation and wayfinding. In: Ninth IEEE International Symposium on Wearable Computers, 2005. Proceedings. 18–21 Oct 2005, pp. 34–37. (2005). doi:10.1109/ISWC.2005.46

  19. 19.

    Fernandes, H., Filipe, V., Costa, P., Barroso, J.: Location based services for the blind supported by RFID technology. Procedia. Comput. Sci. 27, 2–8 (2014)

    Article  Google Scholar 

  20. 20.

    Bin, D., Haitao, Y., Xiaoning, Z., Li, J.: The research on blind navigation system based on RFID. In: International Conference on Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007, 21–25 Sept 2007, pp. 2058–2061. (2007). doi:10.1109/WICOM.2007.514

  21. 21.

    Chumkamon, S., Tuvaphanthaphiphat, P., Keeratiwintakorn, P.: A blind navigation system using RFID for indoor environments. In: 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008. ECTI-CON 2008, 14–17 May 2008, pp. 765–768. (2008). doi:10.1109/ECTICON.2008.4600543

  22. 22.

    Fernandes, H., Faria, J., Paredes, H., Barroso, J.: An integrated system for blind day-to-day life autonomy. In: The Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility, 2011, pp 225–226. ACM (2011)

  23. 23.

    Baus, J., Krüger, A., Wahlster, W.: A resource-adaptive mobile navigation system. Paper Presented at the Proceedings of the 7th International Conference on Intelligent User Interfaces, San Francisco, California, USA (2002)

  24. 24.

    Tsetsos, V., Anagnostopoulos, C., Kikiras, P., Hadjiefthymiades, S.: Semantically enriched navigation for indoor environments. Int. J. Web Grid Serv. 2(4), 453–478 (2006). doi:10.1504/ijwgs.2006.011714

    Article  Google Scholar 

  25. 25.

    Haosheng, H., Gartner, G., Schmidt, M., Yan, L.: Smart environment for ubiquitous indoor navigation. In: International Conference on New Trends in Information and Service Science, 2009. NISS ‘09. June 30 2009–July 2 2009, pp, 176–180. (2009). doi:10.1109/NISS.2009.16

  26. 26.

    Chang, Y.-J., Tsai, S.-K., Wang, T.-Y.: A context aware handheld wayfinding system for individuals with cognitive impairments. Paper Presented at the Proceedings of the 10th International ACM SIGACCESS Conference on Computers and Accessibility, Halifax, Nova Scotia, Canada (2008)

  27. 27.

    Smailagic, A., Martin, R.: Metronaut: a wearable computer with sensing and global communication capabilities. In: First International Symposium on Wearable Computers, 1997. Digest of Papers., 13–14 Oct 1997, pp. 116–122. (1997). doi:10.1109/ISWC.1997.629927

  28. 28.

    Fischer, C., Muthukrishnan, K., Hazas, M., Gellersen, H.: Ultrasound-aided pedestrian dead reckoning for indoor navigation. Paper Presented at the Proceedings of the First ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, San Francisco, California, USA (2008)

  29. 29.

    Höllerer, T., Hallaway, D., Tinna, N., Feiner, S.: Steps toward accommodating variable position tracking accuracy in a mobile augmented reality system. In: Procrrdings of AIMS, 2001. Citeseer, pp. 31–37. (2001)

  30. 30.

    Koide, S., Kato, M.: 3-D human navigation system considering various transition preferences. In: 2005 IEEE International Conference on Systems, Man and Cybernetics, 10–12 Oct 2005, vol. 851, pp. 859–864. (2005). doi:10.1109/ICSMC.2005.1571254

  31. 31.

    Retscher, G.: Pedestrian navigation systems and location-based services. In: 3G 2004. Fifth IEE International Conference on 3G Mobile Communication Technologies, pp. 359–363. (2004). doi:10.1049/cp:20040696

  32. 32.

    Wu, H., Marshall, A., Yu, W.: Path planning and following algorithms in an indoor navigation model for visually impaired. In: Second International Conference on Internet Monitoring and Protection, 2007. ICIMP 2007, pp. 38–38. IEEE (2007)

  33. 33.

    Amemiya, T., Yamashita, J., Hirota, K., Hirose, M.: Virtual leading blocks for the deaf-blind: a real-time way-finder by verbal-nonverbal hybrid interface and high-density RFID tag space. In: Virtual Reality, 2004. Proceedings. IEEE, 27–31 March 2004, pp. 165–287. (2004). doi:10.1109/VR.2004.1310070

  34. 34.

    Brabyn, J., Crandall, W., Gerrey, W.: Talking signs: a remote signage, solution for the blind, visually impaired and reading disabled. In: Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1993, pp. 1309–1310. (1993). doi:10.1109/IEMBS.1993.979150

  35. 35.

    Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The cricket location-support system. Paper presented at the Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, Massachusetts, USA (2000)

  36. 36.

    Ran, L., Helal, S., Moore, S.: Drishti: an integrated indoor/outdoor blind navigation system and service. Paper presented at the Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom’04) (2004)

  37. 37.

    Zheng, P., Ni, L.: Smart Phone and Next Generation Mobile Computing (Morgan Kaufmann Series in Networking (Paperback)). Morgan Kaufmann Publishers Inc., Amsterdam (2005)

    Google Scholar 

  38. 38.

    Etter, R., Specht, M.: Melodious walkabout—implicit navigation with contextualized personal audio contents. In: Adj. Proceedings of Pervasive Computing, 2005. Technology, p. 43 (2005)

  39. 39.

    Helal, A., Moore, S.E., Ramachandran, B.: Drishti: an integrated navigation system for visually impaired and disabled. In: Fifth International Symposium on Wearable Computers, 2001. Proceedings, 2001, pp. 149–156. (2001). doi:10.1109/ISWC.2001.962119

  40. 40.

    Huang, B., Liu, N.: Mobile navigation guide for the visually disabled. Transportation Research Record: Journal of the Transportation Research Board, No. 1885, pp. 28–34. TRB, National Research Council, Washington, D.C. (2004)

  41. 41.

    Arikawa, M., Konomi, S., Ohnishi, K.: Navitime: supporting pedestrian navigation in the real world. IEEE Pervasive Comput. 6(3), 21–29 (2007). doi:10.1109/MPRV.2007.61

    Article  Google Scholar 

  42. 42.

    Retscher, G., Thienelt, M.: NAVIO—a navigation and guidance service for pedestrians. Positioning 1(08), 1 (2004)

    Google Scholar 

  43. 43.

    Mok, E., Retscher, G.: Location determination using WiFi fingerprinting versus WiFi trilateration. J. Locat. Based Serv. 1(2), 145–159 (2007)

    Article  Google Scholar 

  44. 44.

    Faragher, R., Harle, R.: Location fingerprinting with bluetooth low energy beacons. IEEE J. Sel. Areas Commun. 33(11), 2418–2428 (2015)

    Article  Google Scholar 

  45. 45.

    Capp, M., Picton, P.: The optophone: an electronic blind aid. Eng. Sci. Educ. J. 9(3), 137–143 (2000)

    Article  Google Scholar 

  46. 46.

    Ancuti, C., Ancuti, C., Bekaert, P.: ColEnViSon: color enhanced visual sonifier—a polyphonic audio texture and salient scene analysis. In: Proceedings of the Fourth International Conference on Computer Vision Theory and Applications, Vol. 2: VISAPP, (VISIGRAPP 2009), pp 566–572 (2009). doi:10.5220/0001805105660572

  47. 47.

    Praveen, R.G., Paily, R.P.: Blind navigation assistance for visually impaired based on local depth hypothesis from a single image. Procedia Eng. 64, 351–360 (2013)

    Article  Google Scholar 

  48. 48.

    Tian, Y., Yang, X., Yi, C., Arditi, A.: Toward a computer vision-based wayfinding aid for blind persons to access unfamiliar indoor environments. Mach. Vis. Appl. 24(3), 521–535 (2013)

    Article  Google Scholar 

  49. 49.

    Yu, X., Ganz, A.: Audible vision for the blind and visually impaired in indoor open spaces. In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pp. 5110–5113. IEEE (2012)

  50. 50.

    Ruotsalainen, L.: Vision-aided pedestrian navigation for challenging gnss environments. Suomen geodeettisen laitoksen julkaisuja-Publications of the Finnish Geodetic Institute, vol. 151. (2013)

  51. 51.

    Aoki, H., Schiele, B., Pentland, A.: Realtime personal positioning system for a wearable computer. In: The Third International Symposium on Wearable Computers, 1999. Digest of Papers, pp. 37–43. IEEE (1999)

  52. 52.

    Wei, Z., Kosecka, J.: Image based localization in urban environments. In: Third International Symposium on 3D Data Processing, Visualization, and Transmission, 14–16 June 2006, pp. 33–40. (2006). doi:10.1109/3DPVT.2006.80

  53. 53.

    Hile, H., Borriello, G.: Information overlay for camera phones in indoor environments. In: Hightower, J., Schiele, B., Strang, T. (eds.) Location- and Context-Awareness, vol. 4718. Lecture Notes in Computer Science, pp. 68–84. Springer, Berlin (2007). doi:10.1007/978-3-540-75160-1_5

  54. 54.

    Hide, C., Botterill, T., Andreotti, M.: Vision-aided IMU for handheld pedestrian navigation. In: Proceedings of the Institute of Navigation GNSS 2010 Conference, Portland, Oregon (2010)

  55. 55.

    Chekhlov, D., Pupilli, M., Mayol, W., Calway, A.: Robust real-time visual SLAM using scale prediction and exemplar based feature description. In: IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR ‘07, 17–22 June 2007, pp. 1–7. (2007). doi:10.1109/CVPR.2007.383026

  56. 56.

    Zhang, X., Rad, A.B., Wong, Y.-K.: Sensor fusion of monocular cameras and laser rangefinders for line-based simultaneous localization and mapping (SLAM) tasks in autonomous mobile robots. Sensors 12(1), 429–452 (2012)

    Article  Google Scholar 

  57. 57.

    Mulloni, A., Wagner, D., Barakonyi, I., Schmalstieg, D.: Indoor positioning and navigation with camera phones. IEEE Pervasive Comput. 8(2), 22–31 (2009). doi:10.1109/MPRV.2009.30

    Article  Google Scholar 

  58. 58.

    Jirawimut, R., Prakoonwit, S., Cecelja, F., Balachandran, W.: Visual odometer for pedestrian navigation. IEEE Trans. Instrum. Meas. 52(4), 1166–1173 (2003). doi:10.1109/TIM.2003.815996

    Article  Google Scholar 

  59. 59.

    Holzmann, C., Hochgatterer, M.: Measuring distance with mobile phones using single-camera stereo vision. In: 2012 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), 18-21 June 2012, pp. 88–93. (2012). doi:10.1109/ICDCSW.2012.22

  60. 60.

    S-w, Lee, Kang, S., S-w, Lee: A walking guidance system for the visually impaired. Int. J. Pattern Recognit. Artif. Intell. 22(06), 1171–1186 (2008). doi:10.1142/S0218001408006727

    Article  Google Scholar 

  61. 61.

    Anderson, J.D., Dah-Jye, L., Archibald, J.K.: Embedded stereo vision system providing visual guidance to the visually impaired. In: Life Science Systems and Applications Workshop, 2007. LISA 2007. IEEE/NIH, 8–9 Nov 2007, pp. 229–232. (2007). doi:10.1109/LSSA.2007.4400926

  62. 62.

    Penedo, A., Costa, P., Fenandes, H., Pereira, A., Barroso, J.: Image segmentation in systems of stereo vision for visually impaired people. In: DSAI 2009-Proceedings of 2nd International Conference on Software Development for Enhancing Accessibility and Fighting Info-exclusion, pp. 149–156. (2009)

  63. 63.

    Bourbakis, N.: Sensing surrounding 3-D space for navigation of the blind. IEEE Eng. Med. Biol. Mag. 27(1), 49–55 (2008)

    Article  Google Scholar 

  64. 64.

    Sáez, J.M., Escolano, F., Lozano, M.A.: Aerial obstacle detection with 3-D mobile devices. IEEE J Biomed Health Inform 19(1), 74–80 (2015)

    Article  Google Scholar 

  65. 65.

    MicrosoftRobotics: Kinect sensor. https://msdn.microsoft.com/en-us/library/hh438998.aspx (2011). Accessed 16th April 2015

  66. 66.

    Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. In: Khatib, O., Kumar, V., Sukhatme, G. (eds.) Experimental Robotics, vol. 79. Springer Tracts in Advanced Robotics, pp. 477–491. Springer, Berlin (2014). doi:10.1007/978-3-642-28572-1_33

  67. 67.

    Biswas, J., Veloso, M.: Depth camera based indoor mobile robot localization and navigation. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 1697–1702. IEEE (2012)

  68. 68.

    Khoshelham, K., Elberink, S.O.: Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors 12(2), 1437–1454 (2012)

    Article  Google Scholar 

  69. 69.

    Filipe, V., Fernandes, F., Fernandes, H., Sousa, A., Paredes, H., Barroso, J.: Blind navigation support system based on microsoft kinect. Procedia Comput. Sci. 14, 94–101 (2012). doi:10.1016/j.procs.2012.10.011

    Article  Google Scholar 

  70. 70.

    Kammoun, S., Parseihian, G., Gutierrez, O., Brilhault, A., Serpa, A., Raynal, M., Oriola, B., Macé, M.-M., Auvray, M., Denis, M.: Navigation and space perception assistance for the visually impaired: the NAVIG project. Irbm 33(2), 182–189 (2012)

    Article  Google Scholar 

  71. 71.

    Ross, D.A., Blasch, B.B.: Development of a wearable computer orientation system. Pers. Ubiquitous Comput. 6(1), 49–63 (2002)

    Article  Google Scholar 

  72. 72.

    Dakopoulos, D., Bourbakis, N.G.: Wearable obstacle avoidance electronic travel aids for blind: a survey. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 40(1), 25–35 (2010)

    Article  Google Scholar 

  73. 73.

    Brilhault, A., Kammoun, S., Gutierrez, O., Truillet, P., Jouffrais, C.: Fusion of artificial vision and GPS to improve blind pedestrian positioning. In: 2011 4th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 7–10 Feb 2011, pp. 1–5. (2011). doi:10.1109/NTMS.2011.5721061

  74. 74.

    Moreno, M., Shahrabadi, S., José, J., du Buf, J.H., Rodrigues, J.M.: Realtime local navigation for the blind: detection of lateral doors and sound interface. Procedia Comput. Sci. 14, 74–82 (2012)

    Article  Google Scholar 

  75. 75.

    Wu, J., Zhang, J., Yan, J., Liu, W., Song, G.: Design of a vibrotactile vest for contour perception. Int. J. Adv. Robo. Syst. 9, 166 (2012)

    Article  Google Scholar 

  76. 76.

    Nagarajan, R., Yaacob, S., Sainarayanan, G.: Fuzzy-based human vision properties in stereo sonification system for the visually impaired. In: Intelligent Systems and Advanced Manufacturing, 2001. International Society for Optics and Photonics, pp. 525–534. (2001)

  77. 77.

    Murai, Y., Kawahara, M., Tatsumi, H., Araki, T., Miyakawa, M.: Congestion recognition for arm navigation. In: 2010 IEEE International Conference on Systems Man and Cybernetics (SMC), 10–13 Oct 2010, pp. 1530–1535. (2010). doi:10.1109/ICSMC.2010.5642428

  78. 78.

    Coughlan, J., Manduchi, R.: Functional assessment of a camera phone-based wayfinding system operated by blind and visually impaired users. Int. J. Artif. Intell. Tools 18(03), 379–397 (2009)

    Article  Google Scholar 

  79. 79.

    Ivanchenko, V., Coughlan, J., Shen, H.: Crosswatch: A Camera Phone System for Orienting Visually Impaired Pedestrians at Traffic Intersections. Springer, Berlin (2008)

    Google Scholar 

  80. 80.

    Ivanchenko, V., Coughlan, J., Shen, H.: Detecting and locating crosswalks using a camera phone. In: CVPRW’08. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008, pp. 1–8. IEEE (2008)

  81. 81.

    Karacs, K., Radvanyi, M., Gorog, M., Kusnyerik, A., Roska, T.: A mobile visual navigation device: new algorithms for crosswalk and pictogram recognition. In: 2nd International Symposium on Applied Sciences in Biomedical and Communication Technologies, 2009. ISABEL 2009, pp. 1–2. IEEE (2009)

  82. 82.

    Karacs, K., Roska, T.: Route number recognition ot public transport vehicles via the bionic eyeglass. In: 10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA ‘06, 28–30 Aug 2006, pp. 1–6. (2006) doi:10.1109/CNNA.2006.341608

  83. 83.

    Guida, C., Comanducci, D., Colombo, C.: Automatic bus line number localization and recognition on mobile phones—a computer vision aid for the visually impaired. In: Image Analysis and Processing–ICIAP 2011, pp. 323–332. Springer (2011)

  84. 84.

    Hasanuzzaman, F.M., Yang, X., Tian, Y.: Robust and effective component-based banknote recognition for the blind. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 42(6), 1021–1030 (2012)

    Article  Google Scholar 

  85. 85.

    Matusiak, K., Skulimowski, P., Strumillo, P.: Object recognition in a mobile phone application for visually impaired users. In: 2013 The 6th International Conference on Human System Interaction (HSI), pp. 479–484. IEEE (2013)

  86. 86.

    Gomez, J.D., Mohammed, S., Bologna, G., Pun, T.: Toward 3D scene understanding via audio-description: kinect-iPad fusion for the visually impaired. In: The Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 293–294. ACM (2011)

  87. 87.

    Takizawa, H., Yamaguchi, S., Aoyagi, M., Ezaki, N., Mizuno, S.: Kinect cane: an assistive system for the visually impaired based on three-dimensional object recognition. In: 2012 IEEE/SICE International Symposium on System Integration (SII), pp. 740–745. IEEE (2012)

  88. 88.

    Wang, S., Pan, H., Zhang, C., Tian, Y.: RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs. J. Vis. Commun. Image Represent. 25(2), 263–272 (2014)

    Article  Google Scholar 

  89. 89.

    Kang, S., Lee, S.W.: Object detection and classification for outdoor walking guidance system. In: Biologically Motivated Computer Vision, pp. 259–266. Springer, Berlin (2002)

  90. 90.

    Kang, S., Byun, H., S-w, Lee: Real-time pedestrian detection using support vector machines. Int. J. Pattern Recognit. Artif. Intell. 17(03), 405–416 (2003)

    Article  Google Scholar 

  91. 91.

    Alghamdi, S., van Schyndel, R., Khalil, I.: Safe trajectory estimation at a pedestrian crossing to assist visually impaired people. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5114–5117. IEEE (2012)

  92. 92.

    Muthulakshmi, L., Ganesh, A.B.: Bimodal based environmental awareness system for visually impaired people. Procedia Eng. 38, 1132–1137 (2012)

    Article  Google Scholar 

  93. 93.

    Downs, R.M., Stea, D.: Maps in Minds: Reflections on Cognitive Mapping. HarperCollins Publishers, New York (1977)

    Google Scholar 

  94. 94.

    Foulke, E.: Perception, cognition and the mobility of blind pedestrians. In: Spatial Abilities: Development and Physiological Foundations, pp. 55–76. (1982)

  95. 95.

    Loomis, J.M., Klatzky, R.L., Golledge, R.G.: Navigating without vision: basic and applied research. Optom. Vis. Sci. 78(5), 282–289 (2001)

    Article  Google Scholar 

  96. 96.

    Kalia, A.A., Schrater, P.R., Legge, G.E.: Combining path integration and remembered landmarks when navigating without vision. PLoS ONE 8(9), e72170 (2013)

    Article  Google Scholar 

  97. 97.

    Iaria, G., Petrides, M., Dagher, A., Pike, B., Bohbot, V.D.: Cognitive strategies dependent on the hippocampus and caudate nucleus in human navigation: variability and change with practice. J. Neurosci. 23(13), 5945–5952 (2003)

    Article  Google Scholar 

  98. 98.

    Riehle, T., Lichter, P., Giudice, N.: An indoor navigation system to support the visually impaired. In: Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, pp. 4435–4438. IEEE (2008)

  99. 99.

    Lertlakkhanakul, J., Li, Y., Choi, J., Bu, S.: GongPath: development of BIM based indoor pedestrian navigation system. In: Fifth International Joint Conference on INC, IMS and IDC, 2009. NCM’09, pp. 382–388. IEEE (2009)

  100. 100.

    Lyardet, F., Grimmer, J., Muhlhauser, M.: CoINS: context sensitive indoor navigation system. In: Eighth IEEE International Symposium on Multimedia, 2006. ISM’06, pp. 209–218. IEEE (2006)

  101. 101.

    Petrie, H., Johnson, V., Strothotte, T., Raab, A., Fritz, S., Michel, R.: MoBIC: designing a travel aid for blind and elderly people. J. Navig. 49(01), 45–52 (1996)

    Article  Google Scholar 

  102. 102.

    Dingler, T., Lindsay, J., Walker, B.N.: Learnability of sound cues for environmental features: auditory icons, earcons, spearcons, and speech. In: Proceedings of the 14th International Conference on Auditory Display, Paris, France, 2008, pp. 1–6. (2008)

  103. 103.

    Frauenberger, C., Noistering, M. 3D audio interfaces for the blind. Georgia Institute of Technology (2003)

  104. 104.

    Walker, B.N., Lindsay, J.: Navigation performance in a virtual environment with bonephones. In: Proceedings of the International Conference on Auditory Display (ICAD2005), 2005, vol. 3, pp. 1–26. (2005)

  105. 105.

    Manduchi, R., Coughlan, J.: (Computer) vision without sight. Commun. ACM 55(1), 96–104 (2012)

    Article  Google Scholar 

  106. 106.

    Johnson, L.A., Higgins, C.M.: A navigation aid for the blind using tactile-visual sensory substitution. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. EMBS’06, pp. 6289–6292. IEEE (2006)

  107. 107.

    Pissaloux, E., Maingreaud, F., Velazquez, R., Fontaine, E.: Concept of the walking cognitive assistance: experimental validation. AMSE Int. J. Adv. Model. 67, 75–86 (2006). (serie C: automatic control)

    Google Scholar 

  108. 108.

    Technology, B.V.: BrainPort vision technology web page. http://vision.wicab.com (2010). Accessed 23 April 2015

  109. 109.

    Strumillo, P.: Electronic interfaces aiding the visually impaired in environmental access, mobility and navigation. In: 3rd Conference on Human System Interactions (HSI), 2010, pp. 17–24. IEEE (2010)

Download references


The work presented in this paper has been supported by the Project CE4blind—Context extraction for the blind using computer vision, with Project reference UTAP-EXPL/EEI-SII/0043/2014, by the award “Inclusion and Digital Literacy Prize 2015” promoted by the Portuguese ICT and Society Network, and research Grant with reference SFRH/BD/89759/2012. All funding has been granted by the Portuguese Foundation for Science and Technology (FCT).

Author information



Corresponding author

Correspondence to Hugo Fernandes.

Additional information

The original version of this article was revised: The fourth author name Hugo Paredes was missed in the original publication. The list of authors has been corrected.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fernandes, H., Costa, P., Filipe, V. et al. A review of assistive spatial orientation and navigation technologies for the visually impaired. Univ Access Inf Soc 18, 155–168 (2019). https://doi.org/10.1007/s10209-017-0570-8

Download citation


  • Blind
  • Review
  • Assistive technology
  • Location
  • Orientation
  • Navigation
  • Computer vision
  • Accessibility