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Vision-based adaptive assistance and haptic guidance for safe wheelchair corridor following

Published: 01 August 2016 Publication History

Abstract

We devise a low-cost vision-based assistance scheme for wheelchair corridor navigation.Progressive assistance is activated if the wheelchair is in danger, as the user drives manually in a corridor.Natural image features that can be extracted robustly in real-time is employed in order to design the assistive controller.Optimal force feedback, also designed from visual information, is provided using a haptic joystick in order to increase intuitiveness of the system.Experimental results show the feasibility of the system for Commercialization. In case of motor impairments, steering a wheelchair can become a hazardous task. Joystick jerks induced by uncontrolled motions may lead to wall collisions when a user steers a wheelchair along a corridor. This work introduces a low-cost assistive and guidance system for indoor corridor navigation in a wheelchair, which uses purely visual information, and which is capable of providing automatic trajectory correction and haptic guidance in order to avoid wall collisions. A visual servoing approach to autonomous corridor following serves as the backbone to this system. The algorithm employs natural image features which can be robustly extracted in real time. This algorithm is then fused with manual joystick input from the user so that progressive assistance and trajectory correction can be activated as soon as the user is in danger of collision. A force feedback in conjunction with the assistance is provided on the joystick in order to guide the user out of his dangerous trajectory. This ensures intuitive guidance and minimal interference from the trajectory correction system. In addition to being a low-cost approach, it can be seen that the proposed solution does not require an a-priori environment model. Experiments on a robotised wheelchair equipped with a monocular camera prove the capability of the system to adaptively guide and assist a user navigating in a corridor.

References

[1]
B. Krieg-Brückner, D. Crombie, B. Gersdorf, A. Jüptner, M. Lawo, C. Mandel, A.¿B. Martínez, T. Röfer, C. Stahl, Challenges for indoor and outdoor mobility assistance, Technik für ein selbstbestimmtes Leben.
[2]
A. Kokosy, T. Floquet, G. Howells, H. Hu, M. Pepper, C. Donzé, SYSIASS an intelligent powered wheelchair, 2012.
[3]
L. Nordenfelt, Wiley-Blackwell, 2009.
[4]
T. Gomi, A. Griffith, Developing intelligent wheelchairs for the handicapped, Springer Berlin Heidelberg, 1998.
[5]
S.P. Levine, D.A. Bell, L.A. Jaros, R.C. Simpson, Y. Koren, J. Borenstein, The navchair assistive wheelchair navigation system, 1999.
[6]
E. Demeester, E.E.V. Poorten, A. Hüntemann, J. De Schutter, Wheelchair navigation assistance in the FP7 project radhar: objectives and current state, IROS workshop on progress, challenges and future perspectives in navigation and manipulation assistance for robotic wheelchairs, 2012.
[7]
B.D. Argall, Modular and adaptive wheelchair automation, 2014.
[8]
R.A.M. Braga, M. Petry, A.P. Moreira, L.P. Reis, Intellwheels: a development platform for intelligent wheelchairs for disabled people, 2008.
[9]
F. Galán, M. Nuttin, E. Lew, P.W. Ferrez, G. Vanacker, J. Philips, J.D.R. Millán, A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots., Clin. Neurophysiol., 119 (2008) 2159-2169.
[10]
T. Carlson, J. del R. Millan, Brain-controlled wheelchairs: a robotic architecture, IEEE Robot. Autom. Mag., 20 (2013) 65-73.
[11]
S. Thrun, Robotic mapping: a survey, 2002.
[12]
N. Winters, J. Gaspar, G. Lacey, J. Santos-Victor, Omni-directional vision for robot navigation, 2000.
[13]
R. Carelli, C. Soria, O. Nasisi, R. Freire, Stable agv corridor navigation with fused vision-based control signals, 2002.
[14]
J. Toibero, C. Soria, F. Roberti, R. Carelliz, P. Fiorini, Switching visual servoing approach for stable corridor navigation, 2009.
[15]
R.F. Vassallo, H.J. Schneebeli, J. Santos-Victor, Visual servoing and appearance for navigation, Robot. Auton. Syst., 31 (2000) 87-97.
[16]
R.C. Simpson, D. Poirot, F. Baxter, The hephaestus smart wheelchair system, IEEE Trans. Neural Syst. Rehabilit. Eng., 10 (2002) 118-122.
[17]
J. Philips, J. del R. Millan, G. Vanacker, E. Lew, F. Galan, P.W. Ferrez, H.V. Brussel, M. Nuttin, Adaptive shared control of a brain-actuated simulated wheelchair, 2007.
[18]
R. Simpson, S. Levine, Adaptive shared control of a smart wheelchair operated by voice control, 1997.
[19]
A. Escobedo, A. Spalanzani, C. Laugier, Using social cues to estimate possible destinations when driving a robotic wheelchair, 2014.
[20]
E.V. Poorten, E. Demeester, E. Reekmans, J. Philips, A. Huntemann, J. De Schutter, Powered wheelchair navigation assistance through kinematically correct environmental haptic feedback, 2012.
[21]
R. Luo, Force reflective feedback control for intelligent wheelchairs, 1999.
[22]
L. Kitagawa, T. Kobayashi, T. Beppu, K. Terashima, Semi-autonomous obstacle avoidance of omnidirectional wheelchair by joystick impedance control, 2001.
[23]
A. Fattouh, M. Sahnoun, G. Bourhis, Force feedback joystick control of a powered wheelchair: preliminary study, IEEE International Conference on Systems, Man and Cybernetics, Vol. 3 (2004) 2640-2645.
[24]
G. Bourhis, M. Sahnoun, Assisted control mode for a smart wheelchair, 2007.
[25]
F. Chaumette, S. Hutchinson, Visual servo control, part i: basic approaches, IEEE Robot. Autom. Mag., 13 (2006) 82-90.
[26]
F. Pasteau, M. Babel, R. Sekkal, Corridor following wheelchair by visual servoing, 2013.
[27]
F. Pasteau, V. Karakkat-Narayanan, M. Babel, F. Chaumette, A visual servoing approach for autonomous corridor following and doorway passing in a wheelchair, Robot. Auton. Syst., 75 (2015) 28-40.
[28]
F. Pasteau, A. Krupa, M. Babel, Vision-based assistance for wheelchair navigation along corridors, 2014.
[29]
C. Rother, A new approach for vanishing point detection in architectural environments, 2000.
[30]
K. Boulanger, K. Bouatouch, S. Pattanaik, ATIP: a tool for 3d navigation inside a single image with automatic camera calibration, 2006.
[31]
R.G. von Gioi, J. Jakubowicz, J.-M. Morel, G. Randall, LSD: a line segment detector, 2012.
[32]
R. Sekkal, F. Pasteau, M. Babel, B. Brun, I. Leplumey, Simple monocular door detection and tracking, 2013.
[33]
K. Ok, D.-N. Ta, F. Dellaert, Vistas and wall-floor intersection features - enabling autonomous flight in man-made environments, 2012.
[34]
E. Delage, H. Lee, A. Ng, A dynamic bayesian network model for autonomous 3d reconstruction from a single indoor image, 2006.
[35]
O. Kermorgant, F. Chaumette, Combining IBVS and PBVS to ensure the visibility constraint, 2011.
[36]
T. Li, O. Kermorgant, A. Krupa, Maintaining visibility constraints during tele-echography with ultrasound visual servoing, 2012.
[37]
N. Mansard, F. Chaumette, Task sequencing for high-level sensor-based control, IEEE Trans. Robot., 23 (2007) 60-72.
[38]
N. Mansard, A. Remazeilles, F. Chaumette, Continuity of varying-feature-set control laws, IEEE Trans. Autom. Control, 54 (2009) 2493-2505.
[39]
C. Samson, B. Espiau, M.L. Borgne, Oxfored University Press, 1991.
[40]
M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, A.Y. Ng, Ros: an open-source robot operating system, 2009.
[41]
E. Marchand, F. Spindler, F. Chaumette, ViSP for visual servoing: a generic software platform with a wide class of robot control skills, IEEE Robot. Autom. Mag., 12 (2005) 40-52.

Cited By

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  • (2021)Bringing proxemics to walker-assisted gait: using admittance control with spatial modulation to navigate in confined spacesPersonal and Ubiquitous Computing10.1007/s00779-021-01521-826:6(1491-1509)Online publication date: 25-Mar-2021
  • (2019)Remote-operated multimodal interface for therapists during walker-assisted gait rehabilitationProceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction10.5555/3378680.3378771(528-529)Online publication date: 11-Mar-2019

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Information & Contributors

Information

Published In

cover image Computer Vision and Image Understanding
Computer Vision and Image Understanding  Volume 149, Issue C
August 2016
249 pages

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 August 2016

Author Tags

  1. Assistive robotics
  2. Vision-based robotics
  3. Visual servoing
  4. Wheelchair navigation

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View all
  • (2021)Bringing proxemics to walker-assisted gait: using admittance control with spatial modulation to navigate in confined spacesPersonal and Ubiquitous Computing10.1007/s00779-021-01521-826:6(1491-1509)Online publication date: 25-Mar-2021
  • (2019)Remote-operated multimodal interface for therapists during walker-assisted gait rehabilitationProceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction10.5555/3378680.3378771(528-529)Online publication date: 11-Mar-2019

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