{"title":"Mathematical Description of Functional Motion and Application as a Feeding Mode for General Purpose Assistive Robots","authors":"Martin Leroux, Sylvain Brisebois","volume":136,"journal":"International Journal of Biomedical and Biological Engineering","pagesStart":138,"pagesEnd":145,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10008890","abstract":"Eating a meal is among the Activities of Daily Living,
\r\nbut it takes a lot of time and effort for people with physical
\r\nor functional limitations. Dedicated technologies are cumbersome
\r\nand not portable, while general-purpose assistive robots such as
\r\nwheelchair-based manipulators are too hard to control for elaborate
\r\ncontinuous motion like eating. Eating with such devices has not
\r\npreviously been automated, since there existed no description of
\r\na feeding motion for uncontrolled environments. In this paper, we
\r\nintroduce a feeding mode for assistive manipulators, including a
\r\nmathematical description of trajectories for motions that are difficult
\r\nto perform manually such as gathering and scooping food at a
\r\ndefined\/desired pace. We implement these trajectories in a sequence
\r\nof movements for a semi-automated feeding mode which can be
\r\ncontrolled with a very simple 3-button interface, allowing the user
\r\nto have control over the feeding pace. Finally, we demonstrate the
\r\nfeeding mode with a JACO robotic arm and compare the eating
\r\nspeed, measured in bites per minute of three eating methods: a
\r\nhealthy person eating unaided, a person with upper limb limitations
\r\nor disability using JACO with manual control, and a person with
\r\nlimitations using JACO with the feeding mode. We found that the
\r\nfeeding mode allows eating about 5 bites per minute, which should
\r\nbe sufficient to eat a meal under 30min.","references":"[1] D. Foti and J. S. Koketsu, \u201cActivities of daily living,\u201d Pedrettis\r\nOccupational Therapy: Practical Skills for Physical Dysfunction, vol. 7,\r\npp. 157\u2013232, 2013.\r\n[2] I. Naotunna, C. J. Perera, C. Sandaruwan, R. Gopura, and T. D.\r\nLalitharatne, \u201cMeal assistance robots: A review on current status,\r\nchallenges and future directions,\u201d in System Integration (SII), 2015\r\nIEEE\/SICE International Symposium on. IEEE, 2015, pp. 211\u2013216.\r\n[3] W. T. Latt, T. P. Luu, C. Kuah, and A. W. Tech, \u201cTowards an\r\nupper-limb exoskeleton system for assistance in activities of daily living\r\n(adls),\u201d in Proceedings of the international Convention on Rehabilitation\r\nEngineering & Assistive Technology. Singapore Therapeutic, Assistive\r\n& Rehabilitative Technologies (START) Centre, 2014, p. 12.\r\n[4] S. Ishii, S. Tanaka, and F. Hiramatsu, \u201cMeal assistance robot for severely\r\nhandicapped people,\u201d in Robotics and Automation, 1995. Proceedings.,\r\n1995 IEEE International Conference on, vol. 2. IEEE, 1995, pp.\r\n1308\u20131313.\r\n[5] S. W. Brose, D. J. Weber, B. A. Salatin, G. G. Grindle, H. Wang, J. J.\r\nVazquez, and R. A. Cooper, \u201cThe role of assistive robotics in the lives\r\nof persons with disability,\u201d American Journal of Physical Medicine &\r\nRehabilitation, vol. 89, no. 6, pp. 509\u2013521, 2010.\r\n[6] W.-K. Song and J. Kim, \u201cNovel assistive robot for self-feeding,\u201d in\r\nRobotic Systems-Applications, Control and Programming. InTech,\r\n2012.\r\n[7] J. J. Villarreal and S. Ljungblad, \u201cExperience centred design for a robotic\r\neating aid,\u201d in Human-Robot Interaction (HRI), 2011 6th ACM\/IEEE\r\nInternational Conference on. IEEE, 2011, pp. 155\u2013156.\r\n[8] OBI. (2016) Tech specs. (Online). Available:\r\nhttps:\/\/meetobi.com\/tech-specs\/.\r\n[9] M. J. Topping and J. K. Smith, \u201cThe development of handy 1. a robotic\r\nsystem to assist the severely disabled,\u201d Technology and Disability,\r\nvol. 10, no. 2, pp. 95\u2013105, 1999.\r\n[10] M. Topping, \u201cFlexibot\u2013a multi-functional general purpose service robot,\u201d\r\nIndustrial Robot: An International Journal, vol. 28, no. 5, pp. 395\u2013401,\r\n2001.\r\n[11] H. Kwee and C. Stanger, \u201cThe manus robot arm,\u201d Rehabilitation\r\nRobotics Newsletter, vol. 5, no. 2, pp. 1\u20132, 1993.\r\n[12] F. Routhier, P. Archambault, M. Cyr, V. Maheu, M. Lemay, and\r\nI. G\u00b4elinas, \u201cBenefits of jaco robotic arm on independent living and social\r\nparticipation: an exploratory study,\u201d in RESNA Annual Conference, 2014.\r\n[13] V. Maheu, P. S. Archambault, J. Frappier, and F. Routhier, \u201cEvaluation\r\nof the jaco robotic arm: Clinico-economic study for powered wheelchair\r\nusers with upper-extremity disabilities,\u201d in Rehabilitation Robotics\r\n(ICORR), 2011 IEEE International Conference on. IEEE, 2011, pp.\r\n1\u20135.\r\n[14] Y. Cheng, X. Zhao, R. Cai, Z. Li, K. Huang, and Y. Rui,\r\n\u201cSemi-supervised multimodal deep learning for rgb-d object\r\nrecognition.\u201d in IJCAI, 2016, pp. 3345\u20133351.\r\n[15] J. Lahoud and B. Ghanem, \u201c2d-driven 3d object detection in rgb-d\r\nimages,\u201d in Proceedings of the IEEE Conference on Computer Vision\r\nand Pattern Recognition, 2017, pp. 4622\u20134630.\r\n[16] A. Campeau-Lecours, V. Maheu, S. Lepage, H. Lamontagne, S. Latour,\r\nL. Paquet, and N. Hardie, \u201cJaco assistive robotic device: Empowering\r\npeople with disabilities through innovative algorithms,\u201d in Rehabilitation\r\nEngineering and Assistive Technology Society of North America\r\n(RESNA) an-255 nual conference, vol. 14, 2016.\r\n[17] C.-S. Chung, H. Wang, and R. A. Cooper, \u201cFunctional assessment and\r\nperformance evaluation for assistive robotic manipulators: Literature\r\nreview,\u201d The journal of spinal cord medicine, vol. 36, no. 4, pp. 273\u2013289,\r\n2013.\r\n[18] L. V. Herlant, R. M. Holladay, and S. S. Srinivasa, \u201cAssistive\r\nteleoperation of robot arms via automatic time-optimal mode switching,\u201d\r\nin Human-Robot Interaction (HRI), 2016 11th ACM\/IEEE International\r\nConference on. IEEE, 2016, pp. 35\u201342.\r\n[19] X. Xie, M. Jones, and G. Tam, \u201cRecognition, tracking, and optimisation,\u201d\r\nInternational Journal of Computer Vision, vol. 122, no. 3, pp. 409\u2013410,\r\n2017.\r\n[20] H. Jiang, J. P. Wachs, and B. S. Duerstock, \u201cIntegrated vision-based\r\nrobotic arm interface for operators with upper limb mobility\r\nimpairments,\u201d in Rehabilitation Robotics (ICORR), 2013 IEEE\r\nInternational Conference on. IEEE, 2013, pp. 1\u20136.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 136, 2018"}