Force control of lightweight series elastic systems using enhanced disturbance observers

This paper analyzes the control challenges associated to lightweight series elastic systems in force control applications, showing that a low end-point inertia can lead to high sensitivity to environment uncertainties. Where mainstream force control methods fail, this paper proposes a control methodology to enhance the performance robustness of existing disturbance observers (DOBs). The approach is validated experimentally and successfully compared to basic control solutions and state of the art DOB approaches

Myoelectric Control Architectures to Drive Upper Limb Exoskeletons

Myoelectric interfaces are sensing devices based on electromyography (EMG) able to read the electrical activity of motoneurons and muscles. These interfaces can be used to infer movement volition and to control assistive devices. Currently, these interfaces are widely used to control robotic prostheses for amputees, but their use could be beneficial even for people suffering from motor disabilities where the peripheral nervous system is intact and the impairment is only due to the muscles, e.g. muscular dystrophy, myopathies, or ageing. In combination with recent robotic orthoses and exoskeletons, myoelectric interfaces could dramatically improve these patients’ quality of life. Unfortunately, despite a wide plethora of methodologies has been proposed so far, a natural, intuitive, and reliable interface able to follow impaired subjects’ volition is still missing. The first contribution of this work is to provide a review of existing approaches. In this work we found that existing EMG-based control interfaces can be viewed as specific cases of a generic myoelectric control architecture composed by three distinct functional modules: a decoder to extract the movement intention from EMG signals, a controller to accomplish the desired motion through an actual command given to the actuators, and an adapter to connect them. The latter is responsible for translating the signal from decoder’s output to controller’s input domain and for modulating the level of provided assistance. We used this concept to analyse the case of study of linear regression decoders and an elbow exoskeleton. This thesis has the scientific objective to determine how these modules affect performance of EMG-driven exoskeletons and wearer’s fatigue. To experimentally test and compare myoelectric interfaces this work proposes: (1) a procedure to automatically tune the decoder module in order to equally compare or to normalize the decoder output among different sessions and subjects; (2) a procedure to automatically tune gravity compensation even for subjects suffering from severe disabilities, allowing them to perform the experimental tests; (3) a methodology to guide the impaired patients through the experimental session; (4) an evaluation procedure and metrics allowing statistically significant and unbiased comparison of different myoelectric interfaces. A further contribution of this work is the design of an experimental test bed composed by an elbow exoskeleton and by a software framework able to collect EMG signals and make them available to the exoskeleton’s actuators with minimal latency. Using this test bed, we were able to test different myoelectric interfaces based on our architecture, with different modules choices and tunings. We used linear regression decoders calibrated to predict the muscular torque, low-level controllers having torque or velocity as reference, and adapters consisting of a properly dimensioned gain or simple dynamic systems, such as an integrator or a mass-damping system. The results we obtained allow to conclude that EMG-based control is a viable technology to assist muscular weakness patients. Moreover, all the components of the myoelectric control architecture – decoder, adapter, controller, and their tuning – significantly affect the task-based performance measures we collect. Further investigations should be devoted to a methodology to automatically tune all the components, not the decoders only, and to the quantitative study of the effect the adapter has on the regulation of the assistance level and of the tradeoff between speed and accuracy

Robust Force Control of Series Elastic Actuators,

Force-controlled series elastic actuators (SEA) are widely used in novel human-robot interaction (HRI) applications, such as assistive and rehabilitation robotics. These systems are characterized by the presence of the \u201chuman in the loop\u201d, so that control response and stability depend on uncertain human dynamics, including reflexes and voluntary forces. This paper proposes a force control approach that guarantees the stability and robustness of the coupled human-robot system, based on sliding-mode control (SMC), considering the human dynamics as a disturbance to reject. We propose a chattering free solution that employs simple task models to obtain high performance, comparable with second order solutions. Theoretical stability is proven within the sliding mode framework, and predictability is reached by avoiding the reaching phase by design. Furthermore, safety is introduced by a proper design of the sliding surface. The practical feasibility of the approach is shown using an SEA prototype coupled with a human impedance in severe stress tests. To show the quality of the approach, we report a comparison with state-of-the-art second order SMC, passivity-based control and adaptive control solutions

Dynamic movement primitives: volumetric obstacle avoidance

Dynamic Movement Primitives (DMPs) are a framework for learning a trajectory from a demonstration. The trajectory can be learned efficiently after only one demonstration, and it is immediate to adapt it to new goal positions and time duration. Moreover, the trajectory is also robust against perturbations. However, obstacle avoidance for DMPs is still an open problem. In this work, we propose an extension of DMPs to support volumetric obstacle avoidance based on the use of superquadric potentials. We show the advantages of this approach when obstacles have known shape, and we extend it to unknown objects using minimal enclosing ellipsoids. A simulation and experiments with a real robot validate the framework, and we make freely available our implementation

Increasing the precision of the biopsy with robots: two case studies

Robotics is a rapidly advancing field and its introduction in healthcare can have a multitude of benefits for clinical practice. Especially applications depending on the radiologist’s accuracy and precision, such as percutaneous interventions, may profit. Percutaneous interventions are relatively simple and the quality of the procedure increases a lot by introducing robotics due to the improved accuracy and precision. This paper provides the description of two robotic systems for percutaneous interventions: breast biopsy and prostate biopsy. The systems presented here are complete prototypes in an advanced state ready to be tested in clinical practice.https://youtu.be/KZxfRtg0afg https://www.youtube.com/watch?v=AB3Qa6LyHP

Toward autonomous robotic prostate biopsy: a pilot study

Purpose We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and needle positioning. The robot allows executing a targeted biopsy through ultrasound (US) guidance and fusion with magnetic resonance (MR) images, where the target was defined. Methods PROST is a parallel robot with 4 degrees of freedom (DOF) to orient the needle and 1 DOF to rotate the US probe. We reached a calibration error of less than 2 mm, computed as the difference between the needle positioning in robot coordinates and in the US image. The autonomy of the robot is given by the image analysis software, which employs deep learning techniques, the integrated image fusion algorithms and automatic computation of the needle trajectory. For safety reasons, the insertion of the needle is assigned to the doctor. Results System performance was evaluated in terms of positioning accuracy. Tests were performed on a 3D printed object with nine 2-mm spherical targets and on an anatomical commercial phantom that simulates human prostate with three lesions and the surrounding structures. The average accuracy reached in the laboratory experiments was 1.30 ± 0.44 mm in the first test and 1.54 ± 0.34 mm in the second test. Conclusions We introduced a first prototype of a prostate biopsy robot that has the potential to increase the detection of clinically significant prostate cancer and, by including some level of autonomy, to simplify the procedure, to reduce human errors and shorten training time. The use of a robot for the biopsy of the prostate will create the possibility to include also a treatment, such as focal ablation, to be delivered through the same system

COMPLIANT CONTROL OF ELASTIC ACTUATORS FOR HUMAN ROBOT INTERACTION

L'argomento principale di questa tesi \ue8 il controllo di interazione fisica tra uomo e robot. La tesi propone un nuovo approccio alla interazione uomo-robot basato su un modello della dinamica del uomo. Le soluzioni di controllo attualmente esistenti garantiscono la stabilit\ue0 attraverso il concetto di passivit\ue0 in un approccio che modella l'uomo come sistema passivo senza tener conto delle specifiche dinamiche. Pur garantendo la stabilit\ue0 del sistema le tecniche passive non garantiscono la predicibilit\ue0 dell'interazione, a causa appunto delle dinamiche umane non modellate. Questo \ue8 in generale non desiderato, soprattutto se puntiamo a garantire un certo rendimento di controllo, come nel caso di ortesi e protesi robotiche. Questa tesi propone un nuovo approccio di controllo basato sulla modellizzazione della dinamica umana. Nella prima parte vengono analizzati gli i principi consolidati di compliant-control e viene evidenziato il ruolo della compliance nel controllo di interazione. Nella seconda parte vengono proposte due tipi di soluzioni di controllo. La prima \ue8 basato sulla stima on-line delle dinamiche dell'uomo e sul relativo adattamento della legge di controllo. La seconda considera come un disturbo la parte non misurabile della dinamica umana e garantisce la sua reiezione. La stabilit\ue0 e le prestazioni di entrambe le soluzioni sono teoricamente garantite sotto ipotesi realistiche. La validazione sperimentale \ue8 effettuata tramite esperimenti di interazione uomo-robot e mostra evidenti vantaggi degli approcci proposti rispetto alle soluzioni esistenti.This thesis focuses on the control of interaction between a soft robot and a human being. It proposes a novel approach to physical human-robot interaction (pHRI) by explicitly accounting for human dynamics. In fact existing interaction control solutions guarantees stability by regarding the human to a passive system without accounting for its dynamics. Unfortunately such unmodeled dynamics is actually in the loop and influences the interaction unpredictably. As a result the closed loop dynamics is stable but not well defined. This is in general not desired especially if we aim to guarantee a certain control performance as in the case of robotic orthoses and prostheses. Also unpredictable interaction dynamics can be harmful when closing an higher level control loop as the stability region is in turn not well defined. This thesis proposes a novel control approach to the problem. We start from the analysis of existing design and control principles of soft interaction. We outline that physical compliance has the fundamental role of stabilizing force control. Then we propose a novel approach that, taking advantages of compliance, explicitly accounts for the human dynamics in the loop. In particular we propose two kind of control solutions. The first is based on the on-line estimation of human dynamics and on-line adaptation of control law. The second considers certain unmeasurable parts of human dynamics as a disturbance and provides to be insensitive to it. Stability and performance of both solutions are theoretically guaranteed under realistic hypotheses. Experimental validation in a physical human-robot interaction task shows evident advantages of the proposed approaches with respect to existing solutions

An energy efficiency index for elastic actuators during resonant motion

The energetic advantages of series and parallel elastic actuators have been characterized in the literature considering different elastic systems and different tasks. These characterizations usually determine the energy consumption of a specific system during a specific task and generalize poorly. This paper proposes an energetic characterization of elastic actuators, following an analytical approach, rather than a data-driven one. In particular, this work analyzes the energy consumption of elastic actuators during resonant motion and introduces a novel efficiency index. This index characterizes energy consumption as a function of inherent actuator parameters only, generalizing over the specific tasks. The proposed analysis is validated using simulations and experiments, demonstrating its coherence with analytical results

Speech modeling and processing by low-dimensional dynamic glottal models

We discuss the use of low-dimensional physical models of the voice source for speech coding and processing applications. A class of waveform-adaptive dynamic glottal models and parameter tracking procedures are illustrated. The model and analysis procedures are assessed by addressing signal transformations on recorded speech, achievable by fitting the model to the data, and then acting on the physically-oriented parameters of the voice source. The class of models proposed provides in principle a tool for both the estimation of glottal source signals, and the encoding of the speech signal for transformation purposes. The application of this model to time stretching and to frequency control (pitch shifting) is also illustrated. The experiments show that copy synthesis is perceptually almost indistinguishable form the target, and that time stretching and ”pitch extrapolation” effects can be obtained by simple control strategie

Understanding Environment-Adaptive Force Control of Series Elastic Actuators

Series elastic actuators (SEAs) have become fundamental components in robots that physically interact with the surrounding word and with humans. Force control of SEAs is indeed an active area of research. This work refines and improves the stability analysis of the environment-adaptive force controller we previously proposed and proves asymptotic convergence in several cases of practical interest. In particular, we theoretically motivate certain effects which are not adequately explained or covered in our previous work. The analysis reveals an interesting generalization property of the approach, achieved by using a simple and generic model to account for very different environments including stiff contacts, purely inertial loads and soft materials. This is allowed by model parameters with inter-changeable physical meaning: the same parameter describes different physical properties or variables, depending on the kind of interacting environment. In this light, the proposed adaptive controller adapts not only to parameters values, but also to parameter meaning. The analysis also shows that as the environment stiffness decreases, the convergence precision may degrade and a sliding-mode robustification is proposed to overcome the issue. Simulations and experiments are conducted to validate the control convergence in different environments, showing agreement with the theoretical expectation