Multi-physics Modelling of a Compliant Humanoid Robot

In this paper, we discuss some very important features for getting exploitable simulation results for multibody systems, relying on the example of a humanoid robot. First, we provide a comparison of simulation speed and accuracy for kinematics modeling relying on relative vs. absolute coor- dinates. This choice is particularly critical for mechanisms with long serial chains (e.g. legs and arms). Compliance in the robot actuation chain is also critical to enhance the robot safety and en- ergy efficiency, but makes the simulator more sensitive to modeling errors. Therefore, our second contribution is to derive the full electro-mechanical model of the inner dynamics of the compliant actuators embedded in our robot. Finally, we report our reasoning for choosing an appropriate contact library. The recommended solution is to couple our simulator with an open-source contact library offering both accurate and fast full-body contact modeling

MODELLING AND DYNAMIC STABILISATION OF A COMPLIANT HUMANOID ROBOT, CoMan

This dissertation presents the results of a series of studies on dynamic stabilisation of CoMan, which is actuated by series elastic actuators. The main goal of this dissertation is to dynamically stabilise the humanoid robot on the floor by the simplest multivariate feedback control for the purpose of walking. The multivariable scheme is chosen to take into account the joints' interactions, as well as providing a systematic way of designing the feedback system to improve the bandwidth and tracking performance of CoMan's existing PID control. A detailed model is derived which includes all the motors and joints state variables and their multibody interactions which are often ignored in the previous studies on bipedal robots in the literature. The derived dynamic model is then used to design multivariable optimal control feedback and observers with a mathematical proof for the relative stability and robustness of the closed loop system in face of model uncertainties and disturbances. In addition, two decentralized optimal feedback design algorithms are presented that explicitly take the compliant dynamics and the multibody interactions into account while providing the mathematical proof for the stability of the overall system. The purpose of the proposed decentralized control methods is to provide a systematic model based PD-PID design to replace the existing PID controllers which are derived by a trial and error process. Moreover, the challenging constrained and compliant motion of the robot in double support is studied where a novel constrained feedback design is proposed which directly takes the compliance dynamics, interactions and the constraints into account to provide a closed loop feedback tracking system that drives the robot inside the constrained subspace. This method of control is particularly interesting since most control methods applied to closed kinematic chains (such as the double support phase) are over complicated for implementation purposes or have an ad-hoc approach to controller design. In terms of walking trajectory generation, an extension to the ZMP walking trajectory generation is proposed to utilise the CoMan's upper body to tackle the non-minimum phase behaviour that is faced in trajectory generation. Simple inverted pendulum models of walking are then used to study the maximum feasible walking speed and step size where parameters of CoMan are used to provide numerical upper-bounds on the step size and walking speed. Use of straight knee and toe push-off during walking is shown to be beneficial for taking larger step lengths and hence achieving faster walking speeds. Subsequently, the designed tracking systems are then applied to a dynamic walking simulator which is developed during this PhD project to accurately model the compliant walking behaviour of the CoMan. A walking gait is simulated and visualized to show the effectiveness of the developed walking simulator. Moreover, the experimental results and challenges faced during the implementation of the designed tracking control systems are discussed where it is shown that the LQR feedback results in 50\% less control effort and tracking errors in comparison with CoMan's existing independent PID control. This advantage directly affects the feasible walking speed. In addition, a set of standard and repeatable tests for CoMan are designed to quantify and compare the performance of various control system designs. Finally, the conclusions and future directions are pointed out

Dynamic modeling of a 2-DOF cable driven powered ankle-foot prosthesis

Copyright © 2016 by ASME. The first step to study and develop a two Degrees of Freedom (DOF) prosthesis is to derive a dynamic model for simulation and control design. In this paper, the ankle-foot prosthesis has controllable Dorsi-Plantarflexion (DP) and Inversion-Eversion (IE) DOF. We derive a compliant dynamic model for a recently developed ankle-foot prosthesis followed by identification of the actuators, transmission, and prosthetic foot parameters. The resulting model is then verified experimentally and in simulation. Dynamic decoupling of the actuators to the ankle\u27s DP and IE DOF is also investigated using Bode plots. The code used for simulating the prosthesis is provided on GitHub for the community

Gait emulator for evaluation of a powered ankle-foot prosthesis

Copyright © 2017 ASME. In this paper we present an enhanced gait emulator and a novel hybrid control system to test powered ankle-foot prostheses with two degrees of freedom in the sagittal and frontal planes. The gait emulator is a nonlinear and non-smooth system that has to follow a precisely timed set of phases to achieve a human-like periodic gait. Despite the complexity and parameter uncertainties of this five degrees of freedom system, our proposed hybrid control system simplifies the walking control by use of state triggered kinematic events. The control system works in closed loop with kinematic event detection to ensure robust and repeatable walking tests as design parameters are varied. The developed gait emulator can be used to test the prosthesis under various loading conditions and walking speeds

Control of a compliant humanoid robot in double support phase: A geometric approach

Enhancing energy efficiency of bipedal walking is an important research problem that has been approached by design of recently developed compliant bipedal robots such as CoMan. While compliance leads to energy efficiency, it also complicates the walking control system due to further under-actuated degrees of freedom (DoF) associated with the compliant actuators. This problem becomes more challenging as the constrained motion of the robot in double support is considered. In this paper this problem is approached from a multi-variable geometric control aspect to systematically account for the compliant actuators dynamics and constrained motion of the robot in double support phase using a detailed electro-mechanical model of CoMan. It is shown that the formulation of constraint subspace is non-trivial in the case of non-rigid robots. A step-wise numerical algorithm is provided and the effectiveness of the proposed method is illustrated via simulation, using a ten DoF model of CoMan. </jats:p

Estimating the multivariable human ankle impedance in dorsi-plantarflexion and inversion-eversion directions using EMG signals and artificial neural networks

© 2017, Springer Singapore. The use of a suitably designed ankle-foot prosthesis is essential for transtibial amputees to regain lost mobility. A desired ankle–foot prosthesis must be able to replicate the function of a healthy human ankle by transferring the ground reaction forces to the body, absorbing shock during contact, and providing propulsion. During the swing phase of walking, the human ankle is soft and relaxed; however, it hardens as it bears the body weight and provides force for push-off. The stiffness is one of the components of the mechanical impedance, and it varies with muscle activation (Stochastic estimation of human ankle mechanical impedance in medial-lateral direction, 2014, Stochastic estimation of the multivariable mechanical impedance of the human ankle with active muscles, 2010). This study defines the relationship between ankle impedance and the lower extremity muscle activations using artificial neural networks (ANN). We used the Anklebot, a highly backdrivable, safe, and therapeutic robot to apply stochastic position perturbations to the human ankle in the sagittal and frontal planes. A previously proposed system identification method was used to estimate the target ankle impedance to train the ANN. The ankle impedance was estimated with relaxed muscles and with lower leg muscle activations at 10 and 20% of the maximum voluntary contraction (MVC) of each individual subject. Given the root mean squared (rms) of the electromyography (EMG) signals, the proposed ANN effectively predicted the ankle impedance with mean accuracy of 89.8 ± 6.1% in DP and mean accuracy of 88.3 ± 5.7% in IE, averaged across three muscle activation levels and all subjects

Robust and adaptive whole-body controller for humanoids with multiple tasks under uncertain disturbances

Lee J, Dallali H, Jin M, Caldwell D, Tsagarakis N. Robust and adaptive whole-body controller for humanoids with multiple tasks under uncertain disturbances. In: Robotics and Automation (ICRA), 2016 IEEE International Conference on. 2016: 5683--5689

Using lower extremity muscle activity to obtain human ankle impedance in the external–internal direction

© 2017, Springer Nature Singapore Pte Ltd. The human ankle has a critical role in locomotion and estimating its impedance is essential for human gait rehabilitation. The ankle is the first major joint that regulates the contact forces between the human body and the environment, absorbing shocks during the stance, and providing propulsion during walking. Its impedance varies with the level of the muscle activation. Hence, characterizing the complex relation between the ankle impedance and the lower leg’s muscle activation levels may improve our understanding of the neuromuscular characteristics of the ankle. Most ankle–foot prostheses do not have a degree of freedom in the transverse plane, which can cause high amounts of shear stress to be applied to the socket and can lead to secondary injuries. Quantifying the ankle impedance in the transverse plane can guide the design for a variable impedance ankle–foot prosthesis that can significantly reduce the shear stress on the socket. This paper presents the results of applying artificial neural networks (ANN) to learn and estimate the relation between the ankle impedance in the transverse plane under non-load bearing condition using electromyography signals (EMG) from the lower leg muscles. The Anklebot was used to apply pseudorandom perturbations to the human ankle in the transverse plane while the other degrees of freedom (DOF) in the sagittal and frontal planes were constrained. The mechanical impedance of the ankle was estimated using a previously proposed stochastic identification method that describes the ankle impedance as a function of the applied disturbances torques and the ankle motion output. The ankle impedance with relaxed muscles and with the lower leg’s muscle activations at 10 and 20% of the maximum voluntary contraction were estimated. The proposed ANN effectively predicts the ankle impedance within 85% accuracy (±5 Nm/rad absolute) for nine out of ten subjects given the root-mean-squared (rms) of the EMG signals. The main contribution of this paper is to quantify the relationship between lower leg muscle EMG signals and the ankle impedance in the transverse plane to pave the way towards designing and controlling this degree of freedom in a future ankle–foot prosthesis

Design and preliminary evaluation of a two DOFs cable-driven ankle-foot prosthesis with active dorsiflexion-plantarflexion and inversion-eversion

© 2016 Ficanha, Ribeiro, Dallali and Rastgaar. This paper describes the design of an ankle-foot robotic prosthesis controllable in the sagittal and frontal planes. The prosthesis was designed to meet the mechanical characteristics of the human ankle including power, range of motion, and weight. To transfer the power from the motors and gearboxes to the ankle-foot mechanism, a Bowden cable system was used. The Bowden cable allows for optimal placement of the motors and gearboxes in order to improve gait biomechanics such as the metabolic energy cost and gait asymmetry during locomotion. Additionally, it allows flexibility in the customization of the device to amputees with different residual limb sizes. To control the prosthesis, impedance controllers in both sagittal and frontal planes were developed. The impedance controllers used torque feedback from strain gages installed on the foot. Preliminary evaluation was performed to verify the capability of the prosthesis to track the kinematics of the human ankle in two degrees of freedom (DOFs), the mechanical efficiency of the Bowden cable transmission, and the ability of the prosthesis to modulate the impedance of the ankle. Moreover, the system was characterized by describing the relationship between the stiffness of the impedance controllers to the actual stiffness of the ankle. Efficiency estimation showed 85.4% efficiency in the Bowden cable transmission. The prosthesis was capable of properly mimicking human ankle kinematics and changing its mechanical impedance in two DOFs in real time with a range of stiffness sufficient for normal human walking. In dorsiflexion-plantarflexion (DP), the stiffness ranged from 0 to 236 Nm/rad and in inversion-eversion (IE), the stiffness ranged from 1 to 33 Nm/rad