Online Recognition of Environment Properties by Using Bilateral Control

The topic of this thesis is identification of the mechanical impedance of an unknown environment. Through the use of bilateral control based on DOB and RFOB structures, position, speed and force information are gathered and analyzed while performing continuous contact with the environment. The nonlinear Hunt-Crossley model is preferred over the classic Kelvin-Voigt model. Particular attention is given to the precise recognition of contact and the detection of an occurring deformation.ope

Online model estimation and haptic characterization for robotic-assisted minimally invasive surgery

Online soft tissue characterization is important for robotic-assisted minimally invasive surgery (RAMIS) to achieve a precise and stable robotic control with haptic feedback. The traditional linear regression method (i.e. the recursive least square (RLS) method) is inappropriate to handle nonlinear Hunt-Crossley (H-C) model since its linearization process involves unacceptable errors. This thesis presents a new nonlinear estimation method for online soft tissue characterization. To deal with nonlinear and dynamic conditions involved in soft tissue characterization, the approach expands the nonlinearity and dynamics of the H-C model by treating parameter p as an independent variable. Based on this, an unscented Kalman filter (UKF) was adapted for online nonlinear soft tissue characterization. A comparison analysis of the UKF and RLS methods was conducted to validate the performance of the UKF-based method. The UKF-based method suffers from two major problems. The first one is that it requires prior noise statistics of the corresponding system to be precisely known. However, due to uncertainties in the dynamic environment of RAMIS, it is difficult to accurately describe noise characteristics. This leads to biased or even divergent UKF solutions. Therefore, in order to attain accurate estimation results from the UKF-based approach, it is necessary to estimate noise statistics online to restrain the disturbance of noise uncertainty. Secondly, the UKF performance depends on the pre-defined system and measurement models. If the models involve stochastic errors, the UKF-based solution will be unstable. In fact, the measurement model’s accuracy can be guaranteed by using high-precision measurement equipment together with a high volume of available measurement data. On the other hand, the system model is more often involved with the inaccuracy problem. In RAMIS, the system model is a theoretical approximation of the physical contact between robotic tool and biological soft tissue. The approximation is intended to fulfil the requirement of real-time performance in RAMIS. Therefore, it is essential to improve the UKF performance in the presence of system model (the contact model) uncertainty. To address the UKF problem for inaccurate noise statistics, this thesis further presents a new recursive adaptive UKF (RAUKF) method for online nonlinear soft tissue characterization. It was developed, based on the H-C model, to estimate system noise statistics in real-time with windowing approximation. The method was developed under the condition that system noises are of small variation. In order to account for the inherent relationship between the current and previous states of soft tissue deformation involved in RAMIS, a recursive formulation was further constructed by introducing a fading scaling factor. This factor was further modified to accommodate noise statistics of a large variation, which may be caused by rupture events or geometric discontinuities in RAMIS. Simulations and comparison analyses verified the performance of the proposed RAUKF. The second UKF limitation regarding the requirement of the accurate system model was also addressed. A random weighting strong tracking unscented Kalman filter (RWSTUKF) was developed based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This RWSTUKF overcomes the problem of performance degradation in the UKF due to system model errors. It adopts a scaling factor in the predicted state covariance to compensate the inaccuracy of the system model. This scaling factor was derived by combining the orthogonality principle with the random weighting concept to prevent the cumbersome computation from Jacobian matrix and offer the reliable estimation for innovation covariances. Simulation and comparison analyses demonstrated that the proposed RWSTUKF can characterise soft tissue parameters in the presence of system model error for RAMIS in on online mode. Using the proposed methods, a master-slave robotic system has been developed with a nonlinear state observer for soft tissue characterization. Robotic indentation and needle insertion tests conducted to evaluate performances of the proposed methods. Further, a rupture detection approach was established based on the RWSTUKF. It was also integrated into the master-slave robotic system to detect rupture events occurred during needle insertion. The experiment results demonstrated that the RWSTUKF outperforms RLS, UKF and RAUKF for soft tissue characterization

A review of friction models in interacting joints for durability design.

This paper presents a comprehensive review of friction modelling to provide an understanding of design for durability within interacting systems. Friction is a complex phenomenon and occurs at the interface of two components in relative motion. Over the last several decades, the effects of friction and its modelling techniques have been of significant interests in terms of industrial applications. There is however a need to develop a unified mathematical model for friction to inform design for durability within the context of varying operational conditions. Classical dynamic mechanisms model for the design of control systems has not incorporated friction phenomena due to non-linearity behaviour. Therefore, the tribological performance concurrently with the joint dynamics of a manipulator joint applied in hazardous environments needs to be fully analysed. Previously the dynamics and impact models used in mechanical joints with clearance have also been examined. The inclusion of reliability and durability during the design phase is very important for manipulators which are deployed in harsh environmental and operational conditions. The revolute joint is susceptible to failures such as in heavy manipulators these revolute joints can be represented by lubricated conformal sliding surfaces. The presence of pollutants such as debris and corrosive constituents has the potential to alter the contacting surfaces, would in turn affect the performance of revolute joints, and puts both reliability and durability of the systems at greater risks of failure. Key literature is identified and a review on the latest developments of the science of friction modelling is presented here. This review is based on a large volume of knowledge. Gaps in the relevant field have been identified to capitalise on for future developments. Therefore, this review will bring significant benefits to researchers, academics and industrial professionals

Haptic Simulation of Breast Cancer Palpation: A Case Study of Haptic Augmented Reality

ABSTRACT Haptic augmented reality (AR) allows to modulate the haptic properties of a real object by providing virtual haptic feedback. We previously developed a haptic AR system wherein the stiffness of a real object can be augmented with the aid of a haptic interface. To demonstrate its potential, this paper presents a case study for medical training of breast cancer palpation. A real breast model made of soft silicone is augmented with a virtual tumor rendered inside. Haptic stimuli for the virtual tumor are generated based on a contact dynamics model identified via real measurements, without the need of geometric information on the breast. A subjective evaluation confirmed the realism and fidelity of our palpation system

Evaluation of a mesh-based contact model for optimal control problems using automatic differentiation

In recent years, there has been a growing research interest in the field of musculoskeletal gait, with a focus on enhancing the walking ability of older adults and individuals with disabilities due to accidents or illnesses. This research endeavours to comprehend the physical behaviour of muscles, ligaments, and joints that contribute to this movement. The objective of this thesis is to examine and compare the various contact model approaches used to analyse and simulate the contact forces and moments arising on the contact of human joints, particularly in the knee and knee prosthesis. Additionally, the study aims to integrate tangential forces into the original model which only considers normal forces in pressure contact models, and to evaluate and analyse the resulting differences in a tracking problem. To accomplish the objectives of this study, an automatic differentiation tools were employed calculate derivatives to solve an optimal control problem (OCP) using the CasADi library in a Matlab program. Therefore, the model needed to be continuously differentiable. The contact models developed within the group were tested, the results show that the original model had moderate accuracy in predicting lateral knee contact force (��� 2 value of 0.46 and an RMSE of 259.7 N) and better accuracy in predicting medial knee contact force (��� 2 value of 0.62 and an RMSE of 132.6 N). The inclusion of tangential forces in the pressure contact model led to mixed results, such as improved performance in hip flexion, but a decrease in accuracy for predicting both lateral and medial knee contact forces. The study indicates the need for further improvement in mesh-based contact models for knee joint simulation, especially in the inclusion of tangential forces.En els darrers anys, hi ha hagut un interès creixent en la recerca en el camp de la marxa humana i l’estudi de la biomecànica musculoesquelètica, centrada en millorar la capacitat de caminar de les persones grans i les persones amb discapacitats a causa d'accidents o malalties. Aquesta recerca s’esforça per comprendre el comportament físic dels músculs, lligaments i articulacions que contribueixen a aquest moviment. L'objectiu d'aquesta tesi és examinar i comparar les diferents aproximacions del model de contacte utilitzades per analitzar i simular les forces i moments que es produeixen a les superfícies de contacte de les articulacions humanes, especialment al genoll i a una pròtesi de genoll. A més, l'estudi té com a objectiu integrar les forces tangencials al model original, que només considera les forces normals en els models de contacte, i avaluar i analitzar les diferències obtingudes en un problema de seguiment de dades experimentals. Per aconseguir els objectius d'aquest estudi s'ha emprat un mètode de diferenciació automàtica per calcular les derivades de les expressions matemàtiques i resoldre un problema de control òptim (OCP) utilitzant la llibreria CasADi en Matlab. Es van analitzar els models de contacte desenvolupats al grup SIMMA Lab. Els resultats mostren que el model original va tenir una precisió moderada en la predicció de la força de contacte lateral del genoll (valor �� 2 de 0.46 i un RMSE de 259.7 N) i una millor precisió en la predicció de la força de contacte medial del genoll (valor �� 2 de 0.62 i un RMSE de 132.6 N). La inclusió de les forces tangencials en el model de pressió de contacte va donar resultats regulars. Per una banda es va obtenir una millora en la flexió del maluc, però una disminució en la precisió per predir les forces de contacte lateral i medial del genoll. L'estudi indica la necessitat de millores addicionals en els models de contacte basats en malles per a la simulació de l'articulació del genoll, especialment en la integració de les forces tangencials.En los últimos años, ha habido un creciente número de investigaciones en el campo de investigación de la marcha humana y la biomecánica musculoesquelética, con el objetivo de mejorar la capacidad de caminar de personas mayores y personas con discapacidades debido a accidentes o enfermedades. Esta investigación se esfuerza en comprender el comportamiento físico de los músculos, ligamentos y articulaciones que contribuyen a este movimiento. El objetivo de esta tesis es examinar y comparar las diferentes metodologías de modelos de contacto utilizadas para analizar y simular las fuerzas y momentos de contacto en las articulaciones humanas, especialmente en la rodilla y en la prótesis de rodilla. Además, el estudio busca integrar las fuerzas tangenciales en el modelo original, que solo considera las fuerzas normales en los modelos de contacto de presión, y evaluar y analizar las diferencias resultantes en un problema de seguimiento. Para lograr los objetivos de esta investigación, se utilizó un método de diferenciación automática para calcular las derivadas de expresiones matemáticas y resolver un problema de control óptimo (OCP) utilizando la librería CasADi en Matlab. Se analizaron los modelos de contacto desarrollados dentro del grupo SIMMA Lab. Los resultados muestran que el modelo original tuvo una precisión moderada en la predicción de la fuerza de contacto lateral de la rodilla (valor � 2 de 0.46 y un RMSE de 259.7 N) y una mejor precisión en la predicción de la fuerza de contacto medial de la rodilla (valor � 2 de 0.62 y un RMSE de 132.6 N). La inclusión de fuerzas tangenciales en el modelo de contacto dio resultados regulares. Por un lado, se obtuvo un mejor seguimiento de la flexión de cadera, pero por otro lado se obtuvo una disminución en la precisión para predecir tanto la fuerza de contacto lateral como medial de la rodilla. El estudio indica la necesidad de mejorar los modelos de contacto basados en malla para la simulación de la articulación de la rodilla, especialmente en la incorporación de fuerzas tangenciales

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations