Intelligent Service Robotics

, Volume 8, Issue 2, pp 77–92 | Cite as

Navigation assistance and guidance of older adults across complex public spaces: the DALi approach

  • Luigi PalopoliEmail author
  • Antonis Argyros
  • Josef Birchbauer
  • Alessio Colombo
  • Daniele Fontanelli
  • Axel Legay
  • Andrea Garulli
  • Antonello Giannitrapani
  • David Macii
  • Federico Moro
  • Payam Nazemzadeh
  • Pashalis Padeleris
  • Roberto Passerone
  • Georg Poier
  • Domenico Prattichizzo
  • Tizar Rizano
  • Luca Rizzon
  • Stefano Scheggi
  • Sean Sedwards
Original Research Paper


The Devices for Assisted Living(DALi ) project is a research initiative sponsored by the European Commission under the FP7 programmeaiming for the development of a robotic device to assist people with cognitive impairments in navigating complex environments. The project revisits the popular paradigm of the walker enriching it with sensing abilities (to perceive the environment), with cognitive abilities (to decide the best path across the space) and with mechanical, visual, acoustic and haptic guidance devices (to guide the person along the path). In this paper, we offer an overview of the developed system and describe in detail some of its most important technological aspects.


Assistive robotics Navigation Guidance Haptics 


  1. 1.
    Arias A, Hanebeck U (2010) Wide-area haptic guidance: taking the user by the hand. In: Proceedings IEEE/RSJ international conference intelletual robots system, pp 5824–5829Google Scholar
  2. 2.
    Assistants for safe mobility (assam).
  3. 3.
    Bar-Shalom Y, Li X Rong, Kirubarajan T (2001) Estimation with application to tracking and navigation: theory, algorithm and software. Wiley, New YorkCrossRefGoogle Scholar
  4. 4.
    Begault D, Wenzel E, Lee A, Anderson M (2001) Direct comparison of the impact of head tracking, reverberation, and individualized HRTFs on the spatial perception of a virtual speech source. J Audio Eng Soc 49(10):904–916Google Scholar
  5. 5.
    Blauert J (1996) Spatial hearing-revised edition: the psychophysics of human sound localization. MIT press, CambridgeGoogle Scholar
  6. 6.
    Borish J (1984) Extension of the image model to arbitrary polyhedra. J Acoust Soc Am, 75:1827–1836Google Scholar
  7. 7.
    Brown C, Duda R (1998) A structural model for binaural sound synthesis. IEEE Trans Speech Audio Proces 6(5):476–488CrossRefGoogle Scholar
  8. 8.
    Cai C, Ferrari S (2009) Information-driven sensor path planning by approximate cell decomposition. IEEE Trans Syst Man Cybernet Part B Cybernet 39(3):672–689CrossRefGoogle Scholar
  9. 9.
    Choi B-S, Lee J-W, Lee J-J (2008) Localization and map-building of mobile robot based on RFID sensor fusion system. In: Proceedings international conference on industrial informatics (INDIN), Daejeon, Korea, pp 412–417Google Scholar
  10. 10.
    Choi W, Pantofaru C, Savarese S (2013) A general framework for tracking multiple people from a moving camera. IEEE Trans Pattern Anal Mach Intell 35(7):1577–1591CrossRefGoogle Scholar
  11. 11.
    Colombo A, Legay A, Palopoli L, Sedwards S, Fontanelli D (2013) Motion planning in crowds using statistical model checking to enhance the social force model. In: 52nd IEEE conference on decision and control, IEEE, Florence, ItalyGoogle Scholar
  12. 12.
    Coventry L, Targher S et al (2015) Dali deliverable 6.3: system evaluation. Tech. rep., European CommissionGoogle Scholar
  13. 13.
    Delling D, Wagner D (2009) Time-dependent route planning. In: Ahuja R, Möhring R, Zaroliagis C (eds) Robust and online large-scale optimization, vol 5868., Lecture notes in computer scienceSpringer, Berlin, pp 207–230CrossRefGoogle Scholar
  14. 14.
    Demiryurek U, Banaei-Kashani F, Shahabi C (2010) A case for time-dependent shortest path computation in spatial networks. In: Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems., GIS ’10ACM, New York, NY, USA, pp 474–477Google Scholar
  15. 15.
    Dijkstra E (1959) A note on two problems in connexion with graphs. Numer Math 1(1):269–271CrossRefzbMATHMathSciNetGoogle Scholar
  16. 16.
    Ding B, Yu JX, Qin L (2008) Finding time-dependent shortest paths over large graphs. In: Proceedings of the 11th international conference on extending database technology: advances in database technology, EDBT ’08ACM, New York, NY, USA, pp 205–216Google Scholar
  17. 17.
    Endres F, Hess J, Sturm J, Cremers D, Burgard W (2013) 3d mapping with an RGB-D camera. IEEE Trans Robot (T-RO) 30(1):177–187Google Scholar
  18. 18.
    Erp JBFV, Veen HAHCV, Jansen C, Dobbins T (2005) Waypoint navigation with a vibrotactile waist belt. ACM Trans Appl Percept 2(2):106–117CrossRefGoogle Scholar
  19. 19.
    Ess A, Leibe B, Schindler K, Gool LJV (2009) Robust multiperson tracking from a mobile platform. IEEE Trans Pattern Anal Mach Intell 31(10):1831–1846CrossRefGoogle Scholar
  20. 20.
    Felzenszwalb PF, Girshick RB, McAllester DA, Ramanan D (2010) Object detection with discriminatively trained part-based models. IEEE Trans Pattern Anal Mach Intell 32(9):1627–1645CrossRefGoogle Scholar
  21. 21.
    Ferrari V, Marin-Jimenez M, Zisserman A (2008) Progressive search space reduction for human pose estimation. In: Proceedings of the IEEE computer vision and pattern recognition. AlaskaGoogle Scholar
  22. 22.
    Fontanelli D, Giannitrapani A, Palopoli L, Prattichizzo D (2013) Unicycle steering by brakes: a passive guidance support for an assistive cart. In: Proceedings of IEEE international conference on decision and control, IEEE, Florence, Italy, pp 2275–2280. doi: 10.1109/CDC.2013.6760220
  23. 23.
    Foschini L, Hershberger J, Suri S (2014) On the complexity of time-dependent shortest paths. Algorithmica 68(4):1075–1097CrossRefzbMATHMathSciNetGoogle Scholar
  24. 24.
    Fuentes-Pacheco J, Ruiz-Ascencio J, Rendn-Mancha J (2012) Visual simultaneous localization and mapping: a survey. Artif Intell Rev 43(1):55–81Google Scholar
  25. 25.
    Gallagher A, Chen T (2008) Clothing cosegmentation for recognizing people. In: Computer vision and pattern recognition, 2008. CVPR 2008. IEEE conference on, pp 1–8. doi: 10.1109/CVPR.2008.4587481
  26. 26.
    Gemperle F, Hirsch T, Goode A, Pearce J, Siewiorek D, Smailigic A (2003) Wearable vibro-tactile display. Carnegie Mellon UniversityGoogle Scholar
  27. 27.
    Gescheider GA, Bolanowski SJ, Hall KL, Hoffman KE, Verrillo RT (1994) The effects of aging on information-processing channels in the sense of touch: I. Absolute sensitivity. Somatosens Mot Res 11(4):345–357CrossRefGoogle Scholar
  28. 28.
    Ghosh A, Alboul L, Penders J, Jones P, Reed H (2014) Following a robot using a haptic interface without visual feedback. In: Proceedings of international conference on advances in computer-human interactions, pp 147–153Google Scholar
  29. 29.
    Gillespie R, Colgate J, Peshkin M (2001) A general framework for Cobot control. IEEE Trans Robot Autom 17(4):391–401CrossRefGoogle Scholar
  30. 30.
    Goswami A, Peshkin M, Colgate J (1990) Passive robotics: an exploration of mechanical computation. In: Proceedings of the 1990 American control conference, pp 2791–2796Google Scholar
  31. 31.
    Guo D, Wang C, Wanf X (2009) A hierarchical pedestrians motion planning model for heterogeneous crowds simulation. In: International conference on information and automation (ICIA ’09). pp 1363–1367Google Scholar
  32. 32.
    Hahnel D, Burgard W, Fox D, Fishkin K, Philipose M (2004) Mapping and localization with RFID technology. In: Proceedings international conference on robotics and automation, 2004, vol 1. ICRA’04. 2004 IEEE , pp 1015–1020Google Scholar
  33. 33.
    Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, CambridgeGoogle Scholar
  34. 34.
    Helbing D, Molnár P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282–4286CrossRefGoogle Scholar
  35. 35.
    Hirata Y, Hara A, Kosuge K (2007) Motion control of passive intelligent walker using servo brakes. IEEE Trans Robot 23(5):981– 990CrossRefGoogle Scholar
  36. 36.
    Hoppe C, Klopschitz M, Rumpler M, Wendel A, Kluckner S, Bischof H, Reitmayr G (2012) Online feedback for structure-from-motion image acquisition. In: BMVC. pp 1–12Google Scholar
  37. 37.
    Ihaddadene N, Djeraba C (2008) Real-time crowd motion analysis. In: Pattern recognition, 2008. ICPR 2008. 19th IEEE International conference on, pp 1–4Google Scholar
  38. 38.
    Izadi S, Kim D, Hilliges O, Molyneaux D, Newcombe R, Kohli P, Shotton J, Hodges S, Freeman D, Davison A, Fitzgibbon A (2011) Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera. In: Proceedings UIST. pp 559–568Google Scholar
  39. 39.
    Jot JM (1997) Efficient models for reverberation and distance rendering in computer music and virtual audio reality. In: Proceedings of international computer music conferenceGoogle Scholar
  40. 40.
    Karuei I, MacLean KE, Foley-Fisher Z, MacKenzie R, Koch S, El-Zohairy M (2011) Detecting vibrations across the body in mobile contexts. In: Proceedings of international conference on human factors in computing systems. pp 3267–3276Google Scholar
  41. 41.
    Kollmuss A, Agyeman J (2002) Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior? Environ Educat Res 8(3):239–260CrossRefGoogle Scholar
  42. 42.
    Krishnan R, Pugazhenthi S (2014) Mobility assistive devices and self-transfer robotic systems for elderly, a review. Intel Serv Robot 7(1):37–49CrossRefGoogle Scholar
  43. 43.
    Lasovsky Y, Joskowicz L (1999) Motion planning in crowded planar environments. Robotica Null, pp 365–371Google Scholar
  44. 44.
    Latombe J (1991) Robot motion planning. Kluwer Academic Publishers, BostonCrossRefGoogle Scholar
  45. 45.
    Laugier C, Vasquez D, Yguel M, Fraichard T, Aycard O (2008) Geometric and bayesian models for safe navigation in dynamic environments. Intell Serv Robot 1(1):51–72. doi: 10.1007/s11370-007-0004-1 CrossRefGoogle Scholar
  46. 46.
    LaValle SM (2006) Planning algorithms. Cambridge University Press, CambridgeCrossRefzbMATHGoogle Scholar
  47. 47.
    LaValle S, Sharma R (1994) Robot motion planning in a changing, partially predictable environment. In: Proceedings of the 1994 IEEE international symposium on intelligent control. pp 261–266Google Scholar
  48. 48.
    Lee G, Ohnuma T, Chong N (2010) Design and control of JAIST active robotic walker. Intel Serv Robot 3(3):125–135CrossRefGoogle Scholar
  49. 49.
    Lemaire T, Lacroix S, Sola J (2005) A practical 3d bearing-only SLAM algorithm. In: Proceedings of internatinal conference on intelligent robots and systems (IROS), Edmonton, Alberta, Canada, pp 2449–2454Google Scholar
  50. 50.
    Lowe D (2003) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 20:91–110Google Scholar
  51. 51.
    Miura J, Shirai Y (1992) Hierarchical vision-motion planning with uncertainty: local path planning and global route selection. In: Proceedings of the 1992 lEEE/RSJ international conference on intelligent robots and systems, 3:1847–1854Google Scholar
  52. 52.
    Morioka K, Yamanaka S, Hoshino F (2014) Simplified map representation and map learning system for autonomous navigation of mobile robots. Intell Serv Robot 7(1):25–35. doi: 10.1007/s11370-013-0143-5 CrossRefGoogle Scholar
  53. 53.
    Nazemzadeh P, Fontanelli D, Macii D (2013) An indoor position tracking technique based on data fusion for ambient assisted living. In: 2013 IEEE International conference on computational intelligence and virtual environments for measurement systems and applications, Milan, Italy, pp 7–12Google Scholar
  54. 54.
    Nazemzadeh P, Fontanelli D, Macii D, Palopoli L (2014) Indoor positioning of wheeled devices for ambient assisted living: a case study. In: Proceedings IEEE international instrumentation and measurement technology conference (I2MTC), IEEE, Montevideo, Uruguay, pp 1421–1426Google Scholar
  55. 55.
    Nister D, Stewenius H (2006) Scalable recognition with a vocabulary tree. In: Computer vision and pattern recognition, 2006 IEEE computer society conference on, vol 2, pp 2161–2168Google Scholar
  56. 56.
    Panteleris P, Argyros AA (2014) Vision-based SLAM and moving objects tracking for the perceptual support of a smart walker platform. In: Workshop on assistive computer vision and robotics (ACVR 2014), in conjunction with ECCV 2014Google Scholar
  57. 57.
    Rizzon L, Passerone R (2013) Embedded soundscape rendering for the visually impaired. In: Proceedings of the 8th IEEE international symposium on industrial embedded systems, SIES13, pp 101–104. Porto, Portugal. doi: 10.1109/SIES.2013.6601480
  58. 58.
    Rizzon L, Passerone R (2014) Spatial sound rendering for assisted living on an embedded platform. In: De Gloria A (ed) Applications in electronics pervading industry, environment and society, lecture notes in electrical engineering, vol 289, chap 6, pp 61–73. Springer International Publishing. doi: 10.1007/978-3-319-04370-8_6
  59. 59.
    Scheggi S, Aggravi M, Morbidi F, Prattichizzo D (2014) Cooperative human-robot haptic navigation. In: Proceedings of IEEE internatinal conference on robotics and automation. Hong Kong, China, pp 2693–2698Google Scholar
  60. 60.
    Scheggi S, Morbidi F, Prattichizzo D (2014) Human-robot formation control via visual and vibrotactile haptic feedback. IEEE Trans HaptGoogle Scholar
  61. 61.
    Shahab A, Shafait F, Dengel A (2011) Icdar 2011 robust reading competition challenge 2: reading text in scene images. In: Proceedings of the 11th international conference on document analysis and recognition (ICDAR-2011), 11th, September 18–21, Beijing, China, IEEE, pp 1491–1496Google Scholar
  62. 62.
    Sinyukov D, Desmond R, Dickerman M, Fleming J, Schaufeld J, Padir T (2014) Multi-modal control framework for a semi-autonomous wheelchair using modular sensor designs. Intel Serv Robot 7(3):145–155CrossRefGoogle Scholar
  63. 63.
    Sosa LP, Lucas SM, Panaretos A, Sosa L, Tang A, Wong S, Young R (2003) Icdar 2003 robust reading competitions. In: Proceedings of the seventh international conference on document analysis and recognition, pp 682–687, IEEE PressGoogle Scholar
  64. 64.
    The e-no-falls project.
  65. 65.
    The iwalkactive project.
  66. 66.
    Van Cauwenberg J, Van Holle V, Simons D, Deridder R, Clarys P, Goubert L, Nasar J, Salmon J, De Bourdeaudhuij I, Deforche B et al (2012) Environmental factors influencing older adults’ walking for transportation: a study using walk-along interviews. Int J Behav Nutr Phys Act 9(1):85CrossRefGoogle Scholar
  67. 67.
    Viola P, Jones M, Snow D (2003) Detecting pedestrians using patterns of motion and appearance. In: Proceedings of the 9th IEEE international conference on computer vision. Nice, FranceGoogle Scholar
  68. 68.
    Voigt R, Nikolic J, Hurzeler C, Weiss S, Kneip L, Siegwart R (2011) Robust embedded egomotion estimation. In: Intelligent robots and systems (iROS), 2011 IEEE/RSJ international conference on, pp 2694–2699Google Scholar
  69. 69.
    Wang K, Babenko B, Belongie S (2011) End-to-end scene text recognition. In: Proceedings of the 2011 international conference on computer vision., ICCV ’11DC, USA, Washington, pp 1457–1464Google Scholar
  70. 70.
    Wang C, Thorpe C, Hebert M, Thrun S, Durrant-whyte H (2004) Simultaneous localization, mapping and moving object tracking. Int J Robot ResGoogle Scholar
  71. 71.
    Warburton DE, Nicol CW, Bredin SS (2006) Health benefits of physical activity: the evidence. Can Med Assoc J 174(6):801–809CrossRefGoogle Scholar
  72. 72.
    Yao C, Bai X, Liu W, Ma Y, Tu Z (2012) Detecting texts of arbitrary orientations in natural images. In: Proceedings of the 2012 IEEE conference on computer vision and pattern recognition (CVPR), pp 1083–1090. Washington, DC, USAGoogle Scholar
  73. 73.
    Yilmaz A, Javed O, Shah M (2006) Object tracking: a survey. ACM Comput Surv 38(4):45Google Scholar
  74. 74.
    Younes H, Simmons R (2002) Probabilistic verification of discrete event systems using acceptance sampling. In: CAV, vol 2404, pp 23–39. Springer, BerlinGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Luigi Palopoli
    • 1
    Email author
  • Antonis Argyros
    • 2
  • Josef Birchbauer
    • 3
  • Alessio Colombo
    • 1
  • Daniele Fontanelli
    • 1
  • Axel Legay
    • 4
  • Andrea Garulli
    • 5
  • Antonello Giannitrapani
    • 5
  • David Macii
    • 1
  • Federico Moro
    • 1
  • Payam Nazemzadeh
    • 1
  • Pashalis Padeleris
    • 2
  • Roberto Passerone
    • 1
  • Georg Poier
    • 3
  • Domenico Prattichizzo
    • 5
  • Tizar Rizano
    • 1
  • Luca Rizzon
    • 1
  • Stefano Scheggi
    • 5
  • Sean Sedwards
    • 4
  1. 1.Università di TrentoTrentoItaly
  2. 2.Institute of Computer Science (ICS)Foundation for Research and Technology-Hellas (FORTH)HeraklionGreece
  3. 3.SIEMENSGrazAustria
  4. 4.INRIARennesFrance
  5. 5.DIISM, Università di SienaSienaItaly

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