Riccardo Muradore

A PLS-Based Statistical Approach for Fault Detection and Isolation of Robotic Manipulators

In this paper, a statistical approach to fault detection and isolation (FDI) of robot manipulators is presented. It is based on a statistical method called partial least squares (PLS) and on the inverse dynamic model of a robot. PLS is a well-established linear technique in process control for identifying and monitoring industrial plants. Since a robot inverse dynamics can be represented as a linear static model in the dynamical parameters, it is possible to use algorithms and confidence regions developed in statistical decision theory. This approach has several advantages with respect to standard FDI modules: It is strictly related to the algorithm used for identifying the dynamical parameters, it does not need to solve at run time a set of nonlinear differential equations, and the design of a nonlinear observer is not required. This method has been tested on a PUMA 560 simulator, and results of the simulations are discussed.

A Review of Algorithms for Compliant Control of Stiff and Fixed-Compliance Robots

This survey presents the state of the art of basic compliant control algorithms in a unified view of past and present literature. Compliant control is fundamental when dealing with unstructured environments, as in the case of human-robot interaction. This is because it implicitly controls the energy transfer to the environment, providing a safe interaction. In this review, we analyze solutions from traditional robotics, usually involving stiff joints, and recent literature to find common control concepts and differences. To this aim, we bring back every schemas and relative mathematics formulation to a common and simplified scenario. Then, for each schema, we explain its intuitive meaning and report issues raised in the literature. We also propose an expansion of taxonomy to account for recent research.

Mixed H2/H∞ control: the discrete-time case

A stochastic and a mixed stochastic control problem for discrete-time systems are considered and solved. Conditions for existence of a solution are derived, based on the solvability of an equivalent minimax problem. In this framework, it is possible to consider at the same time both stochastic and deterministic disturbances highlighting their mutual effects. The controller can be designed by solving a system of three coupled Riccati equations. Such equations display how the -type minimization problem and the -type constraint influence each other.

An Energy Tank-Based Interactive Control Architecture for Autonomous and Teleoperated Robotic Surgery

Introducing some form of autonomy in robotic surgery is being considered by the medical community to better exploit the potential of robots in the operating room. However, significant technological steps have to occur before even the smallest autonomous task is ready to be presented to the regulatory authorities. In this paper, we address the initial steps of this process, in particular the development of control concepts satisfying the basic safety requirements of robotic surgery, i.e., providing the robot with the necessary dexterity and a stable and smooth behavior of the surgical tool. Two specific situations are considered: the automatic adaptation to changing tissue stiffness and the transition from autonomous to teleoperated mode. These situations replicate real-life cases when the surgeon adapts the stiffness of her/his arm to penetrate tissues of different consistency and when, due to an unexpected event, the surgeon has to take over the control of the surgical robot. To address the first case, we propose a passivity-based interactive control architecture that allows us to implement stable time-varying interactive behaviors. For the second case, we present a two-layered bilateral control architecture that ensures a stable behavior during the transition between autonomy and teleoperation and, after the switch, limits the effect of initial mismatch between master and slave poses. The proposed solutions are validated in the realistic surgical scenario developed within the EU-funded I-SUR project, using a surgical robot prototype specifically designed for the autonomous execution of surgical tasks like the insertion of needles into the human body.

Improving Performance of Networked Control Systems by Using Adaptive Buffering

The performance of networked control systems is strongly affected by time-varying transmission delays. A traditional solution to this problem consists of storing arriving packets in a buffer which smooths delay jitter at the cost of an increased constant delay. The size of the buffer is based on either a long-term or worst case analysis of network behavior leading to poor performance when the instantaneous network behavior is different. To overcome this problem, this paper proposes the following: 1) to adapt the buffer size according to the actual delay variation; 2) to resize buffer content by using cubic spline smoothing which also reduces the signal noise; and 3) to use a Smith predictor at the controller side. Simulation results show that the adaptive buffering strategy reduces delay and packet loss probability while the spline smoothing process improves control performance even in case of constant-size buffers.

A SystemC/Matlab co-simulation tool for networked control systems

Abstract Real-time systems connected through packet networks belong to the family of networked control systems, and they can be easily destabilized by communication delay and packet losses, when they are not properly compensated. The largest part of the solutions available in the literature are mainly based on control and system theory where the parameters of the network are assumed to be given. This classical approach could be improved by designing at the same time the network, e.g., by introducing quality-of-service guarantees as currently done in teleconference applications. Such control/network co-design needs a simulation framework where both aspects are properly and jointly addressed. The paper addresses this topic starting from the discussion of its critical issues, and then proposing an accurate co-simulation tool based on SystemC and Matlab/Simulink. SystemC will be used for the network simulation and protocol design whereas Matlab/Simulink for plant modeling and control design.

Dynamic Calibration of Adaptive Optics Systems: A System Identification Approach

Adaptive optics is used in astronomy to obtain high resolution images, close to diffraction limited, of stars and galaxies with ground telescopes, otherwise blurred by atmospheric turbulence. The measurements of one or more wavefront sensor are used to flatten distorted wavefronts with one or more deformable mirror in a feedback loop. In this brief, we shall report our experience on the problem of building an accurate (dynamical) model of the actuation (deformable mirror) and sensing (wavefront sensor) of adaptive optics system. This will be done adapting state-of-the-art system identification and model reduction techniques to the problem at hand. Our results are based on real data collected under various operating conditions from a demonstrator developed at the European Southern Observatory (ESO), which is now operating in the Paranal Observatory (Chile).

Development of a Cognitive Robotic System for Simple Surgical Tasks

The introduction of robotic surgery within the operating rooms has significantly improved the quality of many surgical procedures. Recently, the research on medical robotic systems focused on increasing the level of autonomy in order to give them the possibility to carry out simple surgical actions autonomously. This paper reports on the development of technologies for introducing automation within the surgical workflow. The results have been obtained during the ongoing FP7 European funded project Intelligent Surgical Robotics (I-SUR). The main goal of the project is to demonstrate that autonomous robotic surgical systems can carry out simple surgical tasks effectively and without major intervention by surgeons. To fulfil this goal, we have developed innovative solutions (both in terms of technologies and algorithms) for the following aspects: fabrication of soft organ models starting from CT images, surgical planning and execution of movement of robot arms in contact with a deformable environment, designing a surgical interface minimizing the cognitive load of the surgeon supervising the actions, intra-operative sensing and reasoning to detect normal transitions and unexpected events. All these technologies have been integrated using a component-based software architecture to control a novel robot designed to perform the surgical actions under study. In this work we provide an overview of our system and report on preliminary results of the automatic execution of needle insertion for the cryoablation of kidney tumours.

Real-time biopsy needle tip estimation in 2D ultrasound images

Ultrasound (US) guided biopsy is a medical procedure routinely performed in clinical practice. This task could be performed by robotic systems to improve the precision in the execution and then the safety for the patient. Both robotic and human procedures could greatly benefit from real-time localization of the needle in US images. This information could guide the robot or the specialists to the correct target point avoiding critical structures. Unfortunately US data provide very low quality images of the needle making this task quite complex, even more if you want to perform the localization on-line during the image acquisition. In this work we present a needle localization method able to extract the needle orientation and the tip position in real time from B-mode US images. To evaluate the performance of the algorithm in a precise way we use an optical tracking system to measure the position and the orientation of the needle and the US probe. In such a way the comparison is not human dependent (i.e. there are no radiologists manually selecting the needle tip) and fully repeatable. The results show an improvement in term of localization accuracy compared to previous works in literature.

A Formal Approach to Cyber-Physical Attacks

We apply formal methods to lay and streamline theoretical foundations to reason about Cyber-Physical Systems (CPSs) and cyber-physical attacks. We focus on integrity and DoS attacks to sensors and actuators of CPSs, and on the timing aspects of these attacks. Our contributions are threefold: (1) we define a hybrid process calculus to model both CPSs and cyber-physical attacks. (2) we define a threat model of cyber-physical attacks and provide the means to assess attack tolerance/vulnerability with respect to a given attack. (3) we formalise how to estimate the impact of a successful attack on a CPS and investigate possible quantifications of the success chances of an attack. We illustrate definitions and results by means of a non-trivial engineering application.