Huihua Zhao
ABSTRACT
Lower-limb prosthesis provide a prime example of cyber-physical systems (CPSs) that interact with humans in a safety critical fashion, and therefore require the synergistic development of sensing, algorithms and controllers. With a view towards better understanding CPSs of this form, this paper presents a methodology for successfully translating nonlinear real-time optimization based controllers from bipedal robots to a novel custom built self-contained powered transfemoral prosthesis: AMPRO. To achieve this goal, we begin by collecting reference human locomotion data via Inertial measurement Units (IMUs). This data forms the basis for an optimization problem that generates virtual constraints, i.e., parametrized trajectories, for the prosthesis that provably yields walking in simulation. Leveraging methods that have proven successful in generating stable robotic locomotion, control Lyapunov function (CLF) based Quadratic Programs (QPs) are utilized to optimally track the resulting desired trajectories. The parameterization of the trajectories is determined through a combination of on-board sensing on the prosthesis together with IMU data, thereby coupling the actions of the user with the controller. Finally, impedance control is integrated into the QP yielding an optimization based control law that displays remarkable tracking and robustness, outperforming traditional PD and impedance control strategies. This is demonstrated experimentally on AMPRO through the implementation of the holistic sensing, algorithm and control framework, with the end result being stable and human-like walking.
- AMPRO walks with the nonlinear real-time optimization controller. http://youtu.be/NxJ7nMsJ63o.Google Scholar
- Comparison of mechanical energy expenditure of joint moments and muscle forces during human locomotion. Journal of Biomechanics, 29(4): 405--415, 1996.Google ScholarCross Ref
- N. Aghasadeghi, H. Zhao, L. J. Hargrove, A. D. Ames, E. J. Perreault, and T. Bretl. Learning impedance controller parameters for lower-limb prostheses. IEEE: IROS, 2013.Google ScholarCross Ref
- A. D. Ames. First steps toward automatically generating bipedal robotic walking from human data. In Book chapter of Robotic Motion and Control, volume 422, pages 89--116, 2011.Google Scholar
- A. D. Ames. Human-inspired control of bipedal robots via control lyapunov functions and quadratic programs. In 16th International conference on Hybrid systems: computation and control, pages 31--32. ACM, 2013. Google ScholarDigital Library
- A. D. Ames, K. Galloway, and J. Grizzle. Control lyapunov functions and hybrid zero dynamics. In Decision and Control, 2012 IEEE Annual Conference on, pages 6837--42.Google Scholar
- D. Atherton and S. Majhi. Limitations of pid controllers. In American Control Conference, pages 3843--3847, 1999.Google Scholar
- C. G. Atkeson and S. Schaal. Robot learning from demonstration. In ICML, pages 12--20, 1997. Google ScholarDigital Library
- S. Au, M. Berniker, and H. Herr. Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits. Neural Networks, 21(4): 654--666, 2008. Google ScholarDigital Library
- J. A. Blaya and H. Herr. Adaptive control of a variable-impedance ankle-foot orthosis to assist drop-foot gait. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 12(1): 24--31, 2004.Google Scholar
- A. Boehler, K. Hollander, T. Sugar, and D. Shin. Design, implementation and test results of a robust control method for a powered ankle foot orthosis (afo). In Robotics and Automation, ICRA, IEEE, pages 2025--2030, 2008.Google Scholar
- W. Flowers and R. Mann. Electrohydraulic knee-torque controller for a prosthesis simulator. ASME J. of Biomechanical Engineering, 99(no. 4): pp. 3--8, 1977.Google ScholarCross Ref
- F. W. C. Grimes D. L. and D. M. Feasibility of an active control scheme for above knee prostheses. ASME J. of Biomechanical Engineering, 99(no. 4): pp. 215--221, 1977.Google Scholar
- J. Hitt, A. M. Oymagil, T. Sugar, K. Hollander, A. Boehler, and J. Fleeger. Dynamically controlled ankle-foot orthosis (dco) with regenerative kinetics: incrementally attaining user portability. In Robotics and Automation, 2007 IEEE International Conference on, pages 1541--1546. IEEE, 2007.Google ScholarCross Ref
- N. Hogan. Impedance control: An approach to manipulation. pages 304--313, 1984.Google Scholar
- Y. Hurmuzlu and D. B. Marghitu. Rigid body collions of planar kinematic chains with multiple contact points. Intl. J. of Robotics Research, 13(1): 82--92, Feb. 1994.Google ScholarCross Ref
- W. Ma, H. Zhao, S. Kolathaya, and A. D. Ames. Human-inspired walking via unified pd and impedance control. In submitted to the IEEE International Conference on Robotics and Automation, 2014.Google Scholar
- J. Nakanishi, J. Morimoto, G. Endo, G. Cheng, S. Schaal, and M. Kawato. Learning from demonstration and adaptation of biped locomotion. Robotics and Autonomous Systems, 47(2): 79--91, 2004.Google ScholarCross Ref
- A. M. Oymagil, J. K. Hitt, T. Sugar, and J. Fleeger. Control of a regenerative braking powered ankle foot orthosis. In Rehabilitation Robotics, 2007. IEEE 10th International Conference on, pages 28--34.Google Scholar
- T. S. Parker, L. O. Chua, and T. S. Parker. Practical numerical algorithms for chaotic systems. Springer New York, 1989. Google ScholarCross Ref
- S. S. Sastry. Nonlinear Systems: Analysis, Stability and Control. Springer, New York, June 1999.Google ScholarCross Ref
- S. Šlajpah, R. Kamnik, and M. Munih. Kinematics based sensory fusion for wearable motion assessment in human walking. Computer methods and programs in biomedicine, 2013. Google ScholarDigital Library
- F. Sup, A. Bohara, and M. Goldfarb. Design and Control of a Powered Transfemoral Prosthesis. The International journal of robotics research, 27(2): 263--273, Feb. 2008. Google ScholarDigital Library
- D. A. Winter. Biomechanics and motor control of human gait: normal, elderly and pathological. 1991.Google Scholar
- D. A. Winter and S. E. Sienko. Biomechanics of below-knee amputee gait. Journal of Biomechanics, 21(5): 361--367, 1988.Google ScholarCross Ref
- H. Zhao and A. Ames. Quadratic program based control of fully-actuated transfemoral prosthesis for flat-ground and up-slope locomotion. In American Control Conference (ACC), 2014, pages 4101--4107, June 2014.Google ScholarCross Ref
- H. Zhao, S. Kolathaya, and A. D. Ames. Quadratic programming and impedance control for transfemoral prosthesis. In International Conference on Robotics and Automation (ICRA) 2014, June.Google ScholarCross Ref
- H. Zhao, W.-L. Ma, M. Zeagler, and A. Ames. Human-inspired multi-contact locomotion with amber2. In Cyber-Physical Systems (ICCPS), 2014 ACM/IEEE International Conference on, pages 199--210, April 2014. Google ScholarDigital Library
- H. Zhao, M. J. Powell, and A. D. Ames. Human-inspired motion primitives and transitions for bipedal robotic locomotion in diverse terrain. Optimal Control Applications and Methods, 2013.Google Scholar
Index Terms
- Realization of nonlinear real-time optimization based controllers on self-contained transfemoral prosthesis
Recommendations
In-socket sensor for transfemoral prosthesis
i-CREATe '13: Proceedings of the 7th International Convention on Rehabilitation Engineering and Assistive TechnologyFor transfemoral amputees, the biomechanical interaction between the stump and the prosthetic socket during the stance and swing phases of gait is critical for a normal-like ambulation. However previous sensors used in microprocessor-controlled ...
Empirical Validation of an Auxetic Structured Foot With the Powered Transfemoral Prosthesis
2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)The toe joint has been studied since it plays a critical role in human ambulation, such as stability, energy storage and propulsion. Despite its critical role, only a few studies have used and tested toe-jointed feet in powered prosthetic walking. In ...
Upslope walking with transfemoral prosthesis using optimization based spline generation
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Powered transfemoral prostheses are robotic systems that aim to restore the mobility of transfemoral amputees by mimicking the functionalities of healthy human legs. The advantage of using a powered prosthetic device is the enhanced performance on various ...
Comments