Human‐inspired motion primitives and transitions for bipedal robotic locomotion in diverse terrain

2014 IEEE International Conference on Robotics and Automation (ICRA)

Kolathaya

Ames

2014

This paper presents a novel optimal control strategy combining control Lyapunov function (CLF) based quadratic programs with impedance control, with the goal of improving both tracking performance and the stability of controllers implemented on transfemoral prosthesis. CLF based quadratic programs have the inherent capacity to optimally track a desired trajectory. This property is used in congruence with impedance control-implemented as a feedforward term-to realize significantly small tracking errors, while simultaneously yielding bipedal walking that is both stable and robust to disturbances. Moreover, instead of experimentally validating this on human subjects, a virtual prosthesis is attached to a robotic testbed, AMBER. The authors claim that the walking of AMBER is human like and therefore form a suitable substitute to human subjects on which a prosthetic control can be tested. Based on this idea, the proposed controller was first verified in simulation, then tested on the physical robot AMBER. The results indicate improved tracking performance, stability, and robustness to unknown disturbances.

Section: B Clf Model Independent Qpmentioning

confidence: 99%

Quadratic programming and impedance control for transfemoral prosthesis

2014 IEEE International Conference on Robotics and Automation (ICRA)

Kolathaya

Ames

2014

“…Utilizing the acceleration-based domain breakdown method discussed in [43], three domains (i.e., subphases) of a single step are considered as motivated by the multicontact walking achieved on the bipedal robot AMBER2 [42]. Based on the actuation type and contact points, we denote the three domains as over-actuated domain, (with the stance heel and swing toe in contact with the ground), fully actuated domain, (with the stance heel and toe in contact with the ground) and under-actuated-domain, (with only stance toe in the ground), as shown in Fig.…”

Section: A Multidomain Human Locomotionmentioning

confidence: 99%

Multicontact Locomotion on Transfemoral Prostheses via Hybrid System Models and Optimization-Based Control

IEEE Trans. Automat. Sci. Eng.

Horn

Reher

et al. 2016

Lower-limb prostheses provide a prime example of cyber-physical systems (CPSs) requiring the synergistic development of sensing, algorithms, and controllers. With a view towards better understanding CPSs of this form, this paper presents a systematic methodology using multidomain hybrid system models and optimization-based controllers to achieve human-like multicontact prosthetic walking on a custom-built prosthesis: AMPRO. To achieve this goal, unimpaired human locomotion data is collected and the nominal multicontact human gait is studied. Inspired by previous work which realized multicontact locomotion on the bipedal robot AMBER2, a hybrid system-based optimization problem utilizing the collected reference human gait as reference is utilized to formally design stable multicontact prosthetic gaits that can be implemented on the prosthesis directly. Leveraging control methods that stabilize bipedal walking robots-control Lyapunov function-based quadratic programs coupled with variable impedance control-an online optimization-based controller is formulated to realize the designed gait in both simulation and experimentally on AMPRO. Improved tracking and energy efficiency are seen when this methodology is implemented experimentally. Importantly, the resulting multicontact prosthetic walking captures the essentials of natural human walking both kinematically and kinetically.Note to Practitioners-Variable impedance control, as one of the most popular prosthetic controllers, has been used widely on powered prostheses with notable success. However, due to the passivity of this controller, heuristic feedback is required to adjust the control parameters for different subjects and motion modes. The end result is extensive testing time for users, coupled with non-optimal performance of prostheses. Motivated by the shortcomings in the current state-of-the-art, this work proposes a novel systematic methodology-including gait generation and optimization-based control based on a multidomain hybrid system-to achieve prosthetic walking for a given subject. aims to improve control optimality and efficiency while potentially reducing clinical tuning. The overarching technology utilized in this paper is the use of nominal human trajectories coupled with formal models and controllers that circumvent the need for excessive hand-tuning. In particular, rather than using a prerecorded trajectory (as is common), this work takes a different approach by using a human-inspired optimization problem to design a human-like gait for the amputee automatically. The proposed optimization framework uses the trajectory of a healthy subject as the reference and is subject to specific constraints (to ensure smooth transitions, torque and angle limitations) such that the output gait is applicable for implementation on the prosthetic device directly. The results of the offline optimization are then utilized to synthesize an online real-time optimization-based feedback controller that allows for pointwise optimal tracking on the prosthesis, thereby impr...

“…where L f is the Lie derivative and A is the dynamic decoupling matrix, which is invertible because of the specific criterion of the outputs selection [29]. By picking u = A −1 (L f + μ), equation (9) becomes:…”

Section: Human-inspired Control Revisitedmentioning

confidence: 99%

Realization of nonlinear real-time optimization based controllers on self-contained transfemoral prosthesis

Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems

Reher

Horn

et al. 2015

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.