207 research outputs found

    Characterisation and State Estimation of Magnetic Soft Continuum Robots

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    Minimally invasive surgery has become more popular as it leads to less bleeding, scarring, pain, and shorter recovery time. However, this has come with counter-intuitive devices and steep surgeon learning curves. Magnetically actuated Soft Continuum Robots (SCR) have the potential to replace these devices, providing high dexterity together with the ability to conform to complex environments and safe human interactions without the cognitive burden for the clinician. Despite considerable progress in the past decade in their development, several challenges still plague SCR hindering their full realisation. This thesis aims at improving magnetically actuated SCR by addressing some of these challenges, such as material characterisation and modelling, and sensing feedback and localisation. Material characterisation for SCR is essential for understanding their behaviour and designing effective modelling and simulation strategies. In this work, the material properties of commonly employed materials in magnetically actuated SCR, such as elastic modulus, hyper-elastic model parameters, and magnetic moment were determined. Additionally, the effect these parameters have on modelling and simulating these devices was investigated. Due to the nature of magnetic actuation, localisation is of utmost importance to ensure accurate control and delivery of functionality. As such, two localisation strategies for magnetically actuated SCR were developed, one capable of estimating the full 6 degrees of freedom (DOFs) pose without any prior pose information, and another capable of accurately tracking the full 6-DOFs in real-time with positional errors lower than 4~mm. These will contribute to the development of autonomous navigation and closed-loop control of magnetically actuated SCR

    A review on model-based and model-free approaches to control soft actuators and their potentials in colonoscopy

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    Colorectal cancer (CRC) is the third most common cancer worldwide and responsible for approximately 1 million deaths annually. Early screening is essential to increase the chances of survival, and it can also reduce the cost of treatments for healthcare centres. Colonoscopy is the gold standard for CRC screening and treatment, but it has several drawbacks, including difficulty in manoeuvring the device, patient discomfort, and high cost. Soft endorobots, small and compliant devices thatcan reduce the force exerted on the colonic wall, offer a potential solution to these issues. However, controlling these soft robots is challenging due to their deformable materials and the limitations of mathematical models. In this Review, we discuss model-free and model-based approaches for controlling soft robots that can potentially be applied to endorobots for colonoscopy. We highlight the importance of selecting appropriate control methods based on various parameters, such as sensor and actuator solutions. This review aims to contribute to the development of smart control strategies for soft endorobots that can enhance the effectiveness and safety of robotics in colonoscopy. These strategies can be defined based on the available information about the robot and surrounding environment, control demands, mechanical design impact and characterization data based on calibration.<br/

    Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

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    Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

    Ultrasound Guidance in Perioperative Care

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    Application of fuzzy type II multi-layer Kalman filter for parameters identification of two-mass drive system

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    The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests

    Design and Implementation of Electromagnetic Actuation System to Actuate Micro/NanoRobots in Viscous Environment

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    The navigation of Micro/Nanorobots (MNRs) with the ability to track a selected trajectory accurately holds significant promise for different applications in biomedicine, providing methods for diagnoses and treatments inside the human body. The critical challenge is ensuring that the required power can be generated within the MNR. Furthermore, ensuring that it is feasible for the robot to travel inside the human body with the necessary power availability. Currently, MNRs are widely driven either by exogenous power sources (light energy, magnetic fields, electric fields, acoustics fields, etc.) or by endogenous energy sources, such as chemical interaction energy. Various driving techniques have been established, including piezoelectric as a driving source, thermal driving, electro-osmotic force driven by biological bacteria, and micro-motors powered by chemical fuel. These driving techniques have some restrictions, mainly when used in biomedicine. External magnetic fields are another potential power source of MNRs. Magnetic fields can permeate deep tissues and be safe for human organisms. As a result, magnetic fields’ magnetic forces and moments can be applied to MNRs without affecting biological fluids and tissues. Due to their features and characteristics of magnetic fields in generating high power, they are naturally suited to control the electromagnetically actuated MNRs in inaccessible locations due to their ability to go through tiny spaces. From the literature, it can be inferred from the available range of actuation technologies that magnetic actuation performs better than other technologies in terms of controllability, speed, flexibility of the working environment, and far less harm may cause to people. Also, electromagnetic actuation systems may come in various configurations that offer many degrees of freedom, different working mediums, and controllability schemes. Although this is a promising field of research, further simulation studies, and analysis, new smart materials, and the development and building of new real systems physically, and testing the concepts under development from different aspects and application requirements are required to determine whether these systems could be implemented in natural clinical settings on the human body. Also, to understand the latest development in MNRs and the actuation techniques with the associated technologies. Also, there is a need to conduct studies and comparisons to conclude the main research achievements in the field, highlight the critical challenges waiting for answers, and develop new research directions to solve and improve the performance. Therefore, this thesis aims to model and analyze, simulate, design, develop, and implement (with complete hardware and software integration) an electromagnetic actuation (EMA) system to actuate MNRs in the sixdimensional (6D) motion space inside a relatively large region of interest (ROI). The second stage is a simulation; simulation and finite element analysis were conducted. COMSOL multi-physics software is used to analyze the performance of different coils and coil pairs for Helmholtz and Maxwell coil configurations and electromagnetic actuation systems. This leads to the following.: • Finite element analysis (FEA) demonstrates that the Helmholtz coils generate a uniform and consistent magnetic field within a targeted ROI, and the Maxwell coils generate a uniform magnetic gradient. • The possibility to combine Helmholtz and Maxwell coils in different space dimensions. With the ability to actuate an MNR in a 6D space: 3D as a position and 3D as orientation. • Different electromagnetic system configurations are proposed, and their effectiveness in guiding an MNR inside a mimicked blood vessel environment was assessed. • Three pairs of Helmholtz coils and three pairs of coils of Maxwell coils are combined to actuate different size MNRs inside a mimicked blood vessel environment and in 6D. Based on the modeling results, a magnetic actuation system prototype that can control different sizes MNRs was conceived. A closed-loop control algorithm was proposed, and motion analysis of the MNR was conducted and discussed for both position and orientation. Improved EMA location tracking along a chosen trajectory was achieved using a PID-based closed-loop control approach with the best possible parameters. Through the model and analysis stage, the developed system was simulated and tested using open- and closed-loop circumstances. Finally, the closedloop controlled system was concluded and simulated to verify the ability of the proposed EMA to actuate an MN under different trajectory tracking examples with different dimensionality and for different sizes of MNRs. The last stage is developing the experimental setup by manufacturing the coils and their base in-house. Drivers and power supplies are selected according to the specifications that actuate the coils to generate the required magnetic field. Three digital microscopes were integrated with the electromagnetic actuation system to deliver visual feedback aiming to track in real-time the location of the MNR in the 6D high viscous fluidic environment, which leads to enabling closed-loop control. The closed-loop control algorithm is developed to facilitate MNR trajectory tracking and minimize the error accordingly. Accordingly, different tests were carried out to check the uniformity of the magnetic field generated from the coils. Also, a test was done for the digital microscope to check that it was calibrated and it works correctly. Experimental tests were conducted in 1D, 2D plane, and 3D trajectories with two different MNR sizes. The results show the ability of the proposed EMA system to actuate the two different sizes with a tracking error of 20-45 µm depending on the axis and the size of the MNR. The experiments show the ability of the developed EMA system to hold the MNR at any point within the 3D fluidic environment while overcoming the gravity effects. A comparison was made between the results achieved (in simulation and physical experiments) and the results deduced from the literature. The comparison shows that the thesis’s outcomes regarding the error and MNR size used are significant, with better performance relative to the MNR size and value of the error
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