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This study theoretically investigates the modeling of spherical catalytic self-phoretic magnetic Janus microrobot (MJR) evolving in uniform viscous flow. A 2-D state-space representation of the MJR is developed, exhibiting a state-dependent-coefficient (SDC) form. To evaluate the consistency of the modeling formalism, a dual Kalman filter (DKF) methodology is employed with respect to experimental results when unknown parameters or uncontrollable inputs are considered. In fact, the self-phoretic thrust mechanism and the magnetodynamics of the MJR are not well-known. SDC-DKF is implemented, and we find that there is good agreement between the dynamics computed from our theoretical predictions and the experimental observations in a wide range of model parameter variations. [ABSTRACT FROM AUTHOR]

Multimicroagent systems are appealing to perform targeted therapy, biosensing, and diagnosis. However on most magnetic platforms, the magnetic field is stationary so all the robots experience the same control input, resulting in an underactuated system. However, to date, the controllability of underactuated microsystems had hardly been addressed. This article thus investigates the system local controllability. This result highlights the necessity for the agents to operate in close vicinity to achieve trajectory tracking along an admissible reference trajectory whose choice is discussed. We then propose a backstepping controller to locally stabilize the nonlinear system. Simulations illustrate this approach efficiency and limitations for different designs of the microrobotic system. [ABSTRACT FROM AUTHOR]

This paper describes the propulsion of the catalytic tubular microjet in confined environments as microchannels and capillaries using the Stokes equations. Especially, the thrust capability of the microjet is outstanding compared with the other microsystems, but remains only partially understood. Studies have identified the internal precursory mechanisms of the propulsion of the microjet: its inner wall catalyzes the dismutation of the fuel and bubbles are then formed. Since the jet is conical, the bubble migrates towards its widest opening. This impulses the propulsion of the microjet towards the opposite direction. However, the precise propellant role of the liquid surrounding the jet remains misunderstood. The same goes for the inner wall of the vessel in which the jet navigates, especially in narrowed environment. This article discusses these aspects in a simplified theoretical framework. Calculations are performed by explicit computation of the Stokes equations. The obtained theoretical results are in good agreement with experimental results reported in the literature. [2017-0202] [ABSTRACT FROM PUBLISHER]

This paper introduces a two-dimensional (2-D) autonomous navigation strategy of a 750- \mu \textm steel microrobot along a complex fluidic vascular network inside the bore of a clinical 3.0-T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation of a microrobot along consecutive channels, the design of autonomous navigation strategy is needed, taking into account the major MRI technological constraints and physiological perturbations, e.g., nonnegligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, and susceptibility artifacts uncertainties. An optimal navigation planning framework based on Pareto optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control, and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750- \mu \textm magnetic microrobots is rendered possible in a complex 2-D centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 \textmms^-1 with average tracking errors below 800 \mu \textm with limited magnetic gradients \pm \text15\ \textmTm^-1 , which is compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade. [ABSTRACT FROM PUBLISHER]

The next generation of telesurgical robotics systems presents significant challenges related to network performance and data security. It is known that packet transmission in wide area networks is a complex stochastic process; thus, low bandwidth as well as high delay, jitter, and packet loss will greatly affect the quality of service (QoS) of teleoperation control, which is unacceptable in this kind of sensitive application. Furthermore, a relevant but more serious issue is the network attacks, particularly denial of service as well as data alteration or disclosure. The main motivation of this study is to deploy suitable security mechanisms while preserving the QoS of network-based bilateral teleoperation. We propose and apply a protocol that secures our teleoperation system while preserving its real-time constraints. More precisely, we present in this paper a bilateral generalized predictive controller coupled to a QoS-friendly IP security protocol. The experimental results demonstrate that the telerobotic system is able to satisfy both QoS and security requirements of real-time and sensitive teleoperation tasks. In fact, our teleoperation security protocol provides priority treatment while preventing attacks and avoiding potential deadline misses due to increased security cost. [ABSTRACT FROM PUBLISHER]

To enhance locoregional therapies for liver cancer treatment, we propose in this study a mathematical model to optimize the transcatheter arterial delivery of therapeutical agents. To maximize the effect of the treatment and minimize adverse effects on the patient, different mathematical models of the tumor growth are considered in this study to find the optimal number of the therapeutic drug-loaded magnetic nanoparticles to be administered. Three types of therapy models are considered, e.g., angiogenesis inhibition therapy, chemotherapy and radiotherapy. We use state-dependent Riccati equations (SDRE) as an optimal control methodology framework to the Hahnfeldt's tumor growth formulation. Based on this, design optimal rules are derived for each therapy to reduce the growth of a tumor through the administration of appropriate dose of antiangiogenic, radio- and chemo-therapeutic agents. Simulation results demonstrate the validity of the proposed optimal delivery approach, leading to reduced intervention time, low drug administration rates and optimal targeted delivery. [ABSTRACT FROM PUBLISHER]