IJAT Vol.11 No.3 pp. 425-432
doi: 10.20965/ijat.2017.p0425


Robotic Assistant for Elderly Care – Development and Evaluation

Natasa Koceska*,†, Saso Koceski*, Vasko Sazdovski**, and Domenico Ciambrone***

*Faculty of Computer Science, University Goce Delcev
Bul. Krste Misirkov 10-A, 2000 Stip, Macedonia

Corresponding author

**Faculty of Electrical Engineering, University Goce Delcev, Stip, Macedonia

***NRG Sys s.r.l., L’Aquila, Italy

October 1, 2016
April 19, 2017
Online released:
April 28, 2017
May 5, 2017
assistive device, telepresence robot, service robot, elderly care, shared control

Robots perform a variety of tasks and serve various purposes in the medical/health and social care sectors. Recently, interest has been growing in developing robotic assistants for health-related care of elderly people. These robotic systems can be used to improve the life of elderly, ensuring healthy and active ageing, thus extending the life expectancy of the elderly in their familiar home environments. In this paper, we present a low-cost telepresence robotic assistant that can assist elderly and professional caregivers in everyday activities. The robot can be operated manually or by using a shared control paradigm. The robot can also be used for interpersonal communication, thus favoring social integration. The developed robot and its navigation capabilities have been evaluated in simulations and experiments, and the evaluation results are reported.

  1. [1] J. F. Engelberger, “Robotics in Service,” MIT Press, Cambridge, 1989.
  2. [2] J. Broekens, M. Heerink, and H. Rosendal, “Assistive social robots in elderly care: A review,” Gerontechnology, Vol.8, pp. 94-103, 2009.
  3. [3] D. Feil-Seifer and M. J. Mataric, “Defining Socially Assistive Robotics,” Proc. of the IEEE Int. Conf. on Rehabilitation Robotics, Chicago, IL, USA, pp. 465-468, June 28 to July 1, 2005.
  4. [4] K. Tanaka, S. Mu, and S. Nakashima, “Meal-Assistance Robot Using Ultrasonic Motor with Eye Interface,” Int. J. of Automation Technology, Vol.8, No.2, pp. 186-192, 2014.
  5. [5] M. E. Pollack, S. Engberg, J. T. Matthews, S. Thrun, L. Brown, D. Colbry, C. Orosz, B. Peintner, S. Ramakrishnan, J. Dunbar-Jacob, C. McCarthy, M. Montemerlo, J. Pineau, and N. Roy, “Pearl: A mobile robotic assistant for the elderly,” AAAI Workshop on Automation as Eldercare, Aug. 2002.
  6. [6] C. Schroeter et al., “Realization and user evaluation of a companion robot for people with mild cognitive impairments,” 2013 IEEE Int. Conf. on Conf. Robotics and Automation (ICRA), pp. 1145-1151, 2013.
  7. [7] Care-o-Bot4 The new modular service robot generation. [Internet] Available from: [Accessed September 20, 2016]
  8. [8] InTouch (2011). InTouch Health Comprehensive Solutions.
    [Accessed September 20, 2016]
  9. [9] A. Sharkey and N. Sharkey, “Children, the elderly, and interactive robots: Anthropomorphism and deception in robot care and companionship,” IEEE Robotics and Automation Magazine, pp. 32-38, 2011.
  10. [10] Kompai R&D robot. [Internet], Available from: http://www.
    [Accessed September 20, 2016]
  11. [11] N. Kawarazaki and T. Yoshidome, “Communication Robot Based on Image Processing and Voice Recognition,” Int. J. of Automation Technology, Vol.5, No.6, pp. 900-907, 2011.
  12. [12] B. N. Uchino, J. T. Cacioppo, and J. K. Kiecolt-Glaser, “The relationship between social support and physiological processes: A review with emphasis on underlying mechanisms and implications for health,” Psychological Bulletin, Vol.119, pp. 488-531, 1996.
  13. [13] S. Cohen and T. A. Willis, “Stress, social support, and the buffering hypothesis,” Psychological Bulletin, Vol.98, pp. 310-357, 1985.
  14. [14] J. L. Moren-Cross and N. Lin, “Handbook of Aging and the Social Sciences,” 6th ed. New York: Elsevier, ch. Social networks and health, 2006.
  15. [15] T. Tsai, Y. Hsu, A. Ma, T. King, and C. Wu, “Developing a Telepresence Robot for Interpersonal Communication with the Elderly in a Home Environment,” Telemedicine and e-Health, Vol.13, No.4, pp. 407-424, 2007.
  16. [16] K. M. Tsui, A. Norton, D. Brooks, H. A. Yanco, and D. Kontak, “Designing Telepresence Robot Systems for Use by People with Special Needs,” Proc. of the Int. Symposium on Quality of Life Technologies 2011: Intelligent Systems for Better Living, held in conjunction with RESNA 2011 as part of FICCDAT, Toronto, Canada, June 6-7, 2011.
  17. [17] A. Cesta, S. Coradeschi, G. Cortellessa, J. Gonzalez, L. Tiberio, and S. von Rump, “Enabling Social Interaction Through Embodiment in ExCITE,” ForItAAL. Second Italian Forum on Ambient Assisted Living, Trento, Italy, Oct. 2010.
  18. [18] A. Kristoffersson, S. Coradeschi, and A. Loutfi, “A Review of Mobile Robotic Telepresence,” Advances in Human-Computer Interaction, Vol.2013, Article ID 902316, 17 pages, 2013.
  19. [19] L. Takayama, E. Marder-Eppstein, H. Harris, and J. Beer, “Assisted driving of a mobile remote presence system; System design and controlled user evaluation,” Int. Conf. on Robotics and Automation (ICRA’11), pp. 1883-1889, 2011.
  20. [20] L. Riano, C. Burbridge, and T. M. McGinnity, “A study of enhanced robot autonomy in telepresence,” Artificial Intelligence and Cognitive Systems, 2011.
  21. [21] J. González-Jiménez, C. Galindo, and J. R. Ruiz-Sarmiento, “Technical improvements of the giraff telepresence robot based on users’ evaluation,” 21st IEEE Int. Symposium on Robot and Human Interactive Communication (Ro-Man ’12), Sep. 2012.
  22. [22] T. Jin, “Obstacle Avoidance of Mobile Robot Based on Behavior Hierarchy by Fuzzy Logic,” Int. J. of Fuzzy Logic and Intelligent Systems, Vol.12, No.3, pp. 245-249, 2012.
  23. [23] S. Jin and B. J. Choi, “Fuzzy Logic System Based Obstacle Avoidance for a Mobile Robot,” FGIT-CA/CES3, 2011.
  24. [24] L. Xu, Y. Chen, and H. Ju, “Autonomous Obstacle Avoidance for Mobile Robot Based on Dynamic Behavior Control,” Computer Engineering, Vol.33, No.14, pp. 180-182, 2007.
  25. [25] B. Huang and G. Cao, “The Path Planning Research for Mobile Robot Based on the Artificial Potential Fild,” Computer Engineering and Application, Vol.27, pp. 26-28, 2006.
  26. [26] C. G. Rusu and I. T. Birou, “Obstacle Avoidance Fuzzy System for Mobile Robot with IR Sensors,” 10th Int. Conf., May 27-29, 2010.
  27. [27] S. K. Pradhan, D. R. Parhi, and A. K. Panda, “Fuzzy logic techniques for navigation of several mobile robots,” Applied Soft Computing, Vol.9, No.1, pp. 290-304, Jan. 2009.
  28. [28] H. J. Yeo and M. H. Sung “Fuzzy Control for the Obstacle Avoidance of Remote Control Mobile Robot,” IEEK 2011, Vol.1, 2011.
  29. [29] K. Jung, J. Kim, and T. Jeon, “Collision Avoidance of Multiple Path-planning using Fuzzy Inference System,” Proc. of KIIS Spring Conf., Vol.19, No.1, 2009.
  30. [30] P. K. Mohanty and D. R. Parh, “A New Intelligent Motion Planning for Mobile Robot Navigation using Multiple Adaptive Neuro-Fuzzy Inference System,” Applied Mathematics & Information Sciences, Vol.8, No.5, pp. 2527-2535, 2014.
  31. [31] R. Tschakarow, S. M. Grigorescu, and A. Gräser, “FRIEND-a dependable semiautonomous rehabilitation,” 2010 41st Int. Symposium on Robotics (ISR) and 2010 6th German Conf. on Robotics (ROBOTIK), pp. 1-7, VDE, 2010.
  32. [32] G. Shuang, N. C. Cheung, K. W. E. Cheng, D. Lei, and L. Xiaozhong, “Skid Steering in 4-Wheel-Drive Electric Vehicle,” 7th Int. Conf. Power Electronics and Drive Systems 2007 (PEDS’07), pp. 1548-1553, 2007.
  33. [33] K. Tchoń, K. Zadarnowska, L. Juszkiewicz, and K. Arent, “Modeling and control of a skid-steering mobile platform with coupled side wheels,” Bulletin of the Polish Academy of Sciences Technical Sciences, Vol.63, No.3, pp. 807-818, 2015.
  34. [34] O. Elshazly, A. Abo-Ismail, H. S. Abbas, and Z. Zyada, “Skid steering mobile robot modeling and control,” 2014 UKACC Int. Conf. on Control (CONTROL), pp. 62-67, 2014.
  35. [35] T. Wang, Y. Wu, J. Liang, C. Han, J. Chen, and Q. Zhao, “Analysis and Experimental Kinematics of a Skid-Steering Wheeled Robot Based on a Laser Scanner Sensor,” Sensors, Vol.15, No.5, pp. 9681-9702, 2015.
  36. [36] Y. Wu, T. Wang, J. Liang, J. Chen, Q. Zhao, X. Yang, and C. Han, “Experimental kinematics modeling estimation for wheeled skid-steering mobile robots,” 2013 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), pp. 268-273, 2013.
  37. [37] K. Kozłowski and D. Pazderski, “Modeling and control of a 4-wheel skid-steering mobile robot,” Int. J. Appl. Math. Comput. Sci., Vol.14, No.4, pp. 477-496, 2004.
  38. [38] M.-L. Huang, Y.-H. Hung, W.-M. Lee, R. K. Li, and T.-H. Wang, “Usage of case-based reasoning, neural network and adaptive neuro-fuzzy inference system classification techniques in breast cancer dataset classification diagnosis,” J. of Medical Systems, Vol.36, No.2, pp. 407-414, 2012.
  39. [39] C. Yildiz, K. Guney, M. Turkmen, and S. Kaya, “Analysis of conductor-backed coplanar waveguides using adaptive-network-based fuzzy inference system models,” Microwave and Optical Technology Letters, Vol.51, No.2, pp. 439-455, 2009.
  40. [40] J.-S. R. Jang, “ANFIS: adaptive-network-based fuzzy inference system,” IEEE Trans. on Systems, Man and Cybernetics, Vol.23, No.3, pp. 665-685, 1993.
Cite this article as:
Natasa Koceska, Saso Koceski, Vasko Sazdovski, and Domenico Ciambrone, “Robotic Assistant for Elderly Care – Development and Evaluation,” Int. J. Automation Technol., Vol.11, No.3, pp. 425-432, 2017
Natasa Koceska, Saso Koceski, Vasko Sazdovski, and Domenico Ciambrone, Int. J. Automation Technol., Vol.11, No.3, pp. 425-432, 2017

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on May. 19, 2018