Conceptual Design of a Gait Rehabilitation Robot

Authors

1 Tarbiat Modares University

2 Hakim Sabzevari University

Abstract

Gait rehabilitation using body weight support on a treadmill is a recommended rehabilitation technique for neurological injuries, such as spinal cord injury. In this paper, a new robotic orthosis is presented for treadmill training. In the presented design the criteria such as low inertia of robot components, backdrivability, high safety and degrees of freedom based on human walking are considered. This robot is composed of a leg exoskeleton for leg control and a segment for pelvis control. In the exoskeleton two degrees of freedom are considered for the hip joint and one for the knee joint. Also two degrees of freedom are considered for the pelvis joints. The inertia of moving components and the required force for the robot motion are measured to evaluate the robot backdrivability and transparency. Further, a walking algorithm is implemented on the robot and is tested on a human subject. Evaluation of the design showed that the robot is suitable for gait rehabilitation exercises.

Keywords

References

F. Horak and L. Nashner, Central programming of postural movements: adaptation to altered supportsurface configurations, Journal of Neurophysiology, Vol. 55(6), (1986), 1369-1381
A.D. Kuo, An optimal control model for analyzing human postural balance, IEEE Transaction Biomedical Engineering, Vol. 42, (1986), 87-101.
C. Liu and C.G. Atkeson, Standing balance control using a trajectory library, IEEE/RSJ Int. Conf. on intelligent robots and systems, Louis, USA, (2009), 3031 -3036.
S. Ito, H. Takishita and M. Sasaki, A study of biped balance control using proportional feedback of ground reaction forces, SISE-ICASE. International Joint Conference, Bexco, Busan, Korea, (2006), 2368-2371.
B. Stephens, Integral Control of Humanoid Balance, The International Conference on Intelligent Robots and Systems (IROS’07), San Diego, CA, (2007).
A. Mahboobin, P. J. Loughlin, M. S. Redfern, S. O. Anderson, C. G. Atkeson, Sensory adaptation human balance control: Lessons for biomimetic robotic bipeds, School of computer science, Carnegie Mellon University, (2008).
M. Abdallah and A. Goswami, A biomechanically motivated two-phase strategy for biped upright balance control, IEEE Int. Conf. on robotics and automation, Barcelona, Spain, (2005), 2008-2013.
C. Yang and Q. Wu, On stabilization of bipedal robots during disturbed standing using the concept of Lyapunov exponents, Robotica, 24(5), (2006), 621 - 624.
C. Yang, Q. Wu and G. Joyce, Effects of constraints on bipedal balance control during standing, Int. J. Humanoid Robotics, 4, (2007), 753-775.
E. Kouchaki, Q. Wu and M. J. Sadigh, Effects of constraints on standing balance control of a bipeds with toe-joints, International Journal ofHumanoid Robotics, 9(3), (2012).
C. K. Ahn, M. C. Lee and S. J. Go, Development of a biped robot with toes to improve gait pattern, IEEE/ASME Int. Conference on Advanced Intelligent Mechatronics, (2003), 729-734.
R. Sellauoti and O. Stasse, Faster and Smoother Walking of humanoid HRP-2 with passive toe-joints, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Beijing, China, (2006), 4909-4914.
K. Yamamoto and T. Sugihara, Toe-joint mechanism using parallel four-bar linkage enabling humanlike multiple support at toe pad and toe tip, Int. Conf. on Humanoid Robots, Pittsburgh, USA, (2007), 410-415.
D. Tlalolini, C. Chevallereau, and Y. Aoustin, Human-like walking: optimal motion of a bipedal robot with toe-rotation motion, IEEE/ASME Transactions on Mechatronics, 16, (2011), 310-320.
E. Kouchaki, M.J. Sadigh, Effect of Toe-Joint Bending on Biped Gait Performance, IEEE Int. Conf. on robotics and biomimetics, Tianjin, China, (2010), 697-702.
M. Cannon, Model predictive control, Lecture notes, Oxford University, (2011).
A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano, Determining Lyapunov Exponents from a Time Series, Physics D, 16, (1985), 285317, 1985.
C. Yang, Q. Wu, On stability analysis via Lyapunov exponents calculated from a time series using nonlinear mapping-a case study, Nonlinear Dynamics, Vol. 59, (2010), 239-257.
International Journal of Robotics, Theory and Applications
Volume 4, Issue 1
June 2015
Pages 55-61

Files

Share

How to cite

Statistics