Abstract
A way-finding system in an indoor environment consists of several components: localization, representation, path planning, and interaction. For each component, numerous relevant techniques have been proposed. However, deploying feasible techniques, particularly in real scenarios, remains challenging. In this paper, we describe a functional way-finding system deployed on a mobile robot to assist visual impairments (VI). The proposed system deploys state-of-the-art techniques that are adapted to the practical issues at hand. First, we adapt an outdoor visual odometry technique to indoor use by covering manual markers or stickers on ground-planes. The main purpose is to build reliable travel routes in the environment. Second, we propose a procedure to define and optimize the landmark/representative scenes of the environment. This technique handles the repetitive and ambiguous structures of the environment. In order to interact with VI people, we deploy a convenient interface on a smart phone. Three different indoor scenarios and thirteen subjects are conducted in our evaluations. Our experimental results show that VI people, particularly VI pupils, can find the right way to requested targets.



















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Notes
Nguyen Dinh Chieu Blind School, Hanoi
5nd floor of Ta Quang Buu Library, HUST
10th International Research Institute MICA, HUST
References
Alcantarilla FP (2011) Vision based localization: from humanoid robots to visually impaired people. Ph.D Thesis
Bailey T, Durrant-Whyte H (2006) Simultaneous localization and mapping (slam): part ii. IEEE Robot Autom Mag 13(3):108–117
Bigham J, Jayant C, Miller A (2010) White: Vizwiz::locateit - enabling blind people to locate objects in their environment. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp 65–72
Chow C, Liu C (1968) Approximating discrete probability distributions with dependence trees. IEEE Trans Inf Theory 14(3):462–467
Cummins M, Newman P (2008) Fab-map: Probabilistic localization and mapping in the space of apperance. Int J Robot Res 27(6):647–665
Dakopoulos D, Bourbakis NG (2010) Wearable obstacle avoidance electronic travel aids for blind: a survey. IEEE Trans Syst, Man, Cybernet Part C: Appl Rev 40 (1):25–35
Endres H, Feiten W, Lawitzky G (1998) Field test of a navigation system: Autonomous cleaning in supermarkets. In: the Proceeding of International Conference on Robotics and Automation. IEEE
Fallah N, Apostolopoulos I, Bekris K, Folmer E (2013) Indoor human navigation systems - a survey. Interact Comput 25(1):21–33
Fraundorfer F, Scaramuzza D (2012) Visual odometry : Part ii: Matching, robustness, optimization, and applications. IEEE Robot Autom Mag 19(2):78–90
Hamme D, Veelaert P (2011) Robust visual odometry using uncertainty models. Proc Adv Concepts Intell Vis Syst 6915:1–12
Hart PE, Nilsson NJ, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cybern 4(2):100–107
Helal A, Moore SE, Ramachandran B (2001) Drishti: An integrated navigation system for visually impaired and disabled. In: Proceedings. Fifth International Symposium on Wearable Computers, 2001. IEEE, pp 149–156
King S, Weiman C (1990) Helpmate autonomous mobile robot navigation system. In: the Proceeding of the SPIE Conference on Mobile Robots, pp 190–198
Korf RE (1985) Iterative-deepening-a: an optimal admissible tree search. In: Proceedings of the 9th international joint conference on Artificial intelligence-Volume 2. Morgan Kaufmann Publishers Inc, pp 1034–1036
Kulyukin V, Gharpure C (2006) Nicholson: Robot assisted way-finding for the visually impaired in structured indoor environments. Auton Robot 21:29–41
Kulyukin V, Gharpure C, Nicholson J, Pavithran S (2004) Rfid in robot-assisted indoor navigation for the visually impaired. In: Proceedings. 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. (IROS 2004), vol 2. IEEE, pp 1979–1984
Lacey G, Dawson-Howe K (1998) The application of robotics to a mobility aid for the elderly blind. Robot Auton Syst 23:245–252
LaMarca A, Brunette W, Koizumi D (2002) Making sensor networks practical with robots. In: the Proceeding of International Conference on Pervasive Computing. IEEE
Lehel P, Hemayed E, Farag A (1999) Robot assisted way-finding for the visually impaired in structured indoor environments. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol 2
Liu JJ, Phillips C, Daniilidis K (2010) Video-based localization without 3d mapping for the visually impaired. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, pp 23–30
Loomis JM, Golledge RD (2001) Klatzky: Gps-based navigation systems for the visually impaired. Fundamentals of wearable computers and augmented reality, pp 429–446
Marion AH, Micheal AJ (2008) Assistive Technology for Visually Impaired and Blind People. Springer
Murali VN, Coughlan JM (2013) Smartphone-based crosswalk detection and localization for visually impaired pedestrians. In: 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW). IEEE, pp 1–7
Newman P, Ho K (2005) Slam-loop closing with visually salient features. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005. ICRA 2005. IEEE, pp 635–642
Nister D, Stewenius H (2006) Scalable recognition with a vocabulary tree. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol 2. IEEE, pp 2161–2168
Pradeep V, Medioni G, Weiland J (2010) Robot vision for the visually impaired. In: Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on. IEEE, pp 15–22
Pradeep V, Medioni G, Weiland J (2010) Robot vision for the visually impaired. In: Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on. IEEE, pp 15–22
Schindler G, Brown M, Szeliski R (2007) City-scale location recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR ’07, pp 1–7
Sivic J, Zisserman A (2003) Video google: a text retrieval approach to object matching in videos. In: Proceedings. Ninth IEEE International Conference on Computer Vision, 2003, vol 2, pp 1470–1477
Sunderhauf N, Protzel P (2011) Brief-gist-closing the loop by simple means. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, pp 1234–1241
Winlock T, Christiansen E, Belongie S (2010) Toward real-time grocery detection for the visually impaired. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, pp 49–56
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This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number FWO.102.2013.08.
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Nguyen, QH., Vu, H., Tran, TH. et al. Developing a way-finding system on mobile robot assisting visually impaired people in an indoor environment. Multimed Tools Appl 76, 2645–2669 (2017). https://doi.org/10.1007/s11042-015-3204-2
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DOI: https://doi.org/10.1007/s11042-015-3204-2