1,102 research outputs found

    Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots

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    Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm.Comment: submitted to IROS 201

    A robot hand testbed designed for enhancing embodiment and functional neurorehabilitation of body schema in subjects with upper limb impairment or loss.

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    Many upper limb amputees experience an incessant, post-amputation "phantom limb pain" and report that their missing limbs feel paralyzed in an uncomfortable posture. One hypothesis is that efferent commands no longer generate expected afferent signals, such as proprioceptive feedback from changes in limb configuration, and that the mismatch of motor commands and visual feedback is interpreted as pain. Non-invasive therapeutic techniques for treating phantom limb pain, such as mirror visual feedback (MVF), rely on visualizations of postural changes. Advances in neural interfaces for artificial sensory feedback now make it possible to combine MVF with a high-tech "rubber hand" illusion, in which subjects develop a sense of embodiment with a fake hand when subjected to congruent visual and somatosensory feedback. We discuss clinical benefits that could arise from the confluence of known concepts such as MVF and the rubber hand illusion, and new technologies such as neural interfaces for sensory feedback and highly sensorized robot hand testbeds, such as the "BairClaw" presented here. Our multi-articulating, anthropomorphic robot testbed can be used to study proprioceptive and tactile sensory stimuli during physical finger-object interactions. Conceived for artificial grasp, manipulation, and haptic exploration, the BairClaw could also be used for future studies on the neurorehabilitation of somatosensory disorders due to upper limb impairment or loss. A remote actuation system enables the modular control of tendon-driven hands. The artificial proprioception system enables direct measurement of joint angles and tendon tensions while temperature, vibration, and skin deformation are provided by a multimodal tactile sensor. The provision of multimodal sensory feedback that is spatiotemporally consistent with commanded actions could lead to benefits such as reduced phantom limb pain, and increased prosthesis use due to improved functionality and reduced cognitive burden

    A Magnetic Localization Technique Designed for use with Magnetic Levitation Systems.

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    M.S. Thesis. University of Hawaiʻi at Mānoa 2017

    Achieving commutation control of an MRI-powered robot actuator

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    Actuators that are powered, imaged, and controlled by magnetic resonance (MR) scanners could inexpensively provide wireless control of MR-guided robots. Similar to traditional electric motors, the MR scanner acts as the stator and generates propulsive torques on an actuator rotor containing one or more ferrous particles. Generating maximum motor torque while avoiding instabilities and slippage requires closed-loop control of the electromagnetic field gradients, i.e., commutation. Accurately estimating the position and velocity of the rotor is essential for high-speed control, which is a challenge due to the low refresh rate and high latency associated with MR signal acquisition. This paper proposes and demonstrates a method for closed-loop commutation based on interleaving pulse sequences for rotor imaging and rotor propulsion. This approach is shown to increase motor torque and velocity, eliminate rotor slip, and enable regulation of rotor angle. Experiments with a closed-loop MR imaging actuator produced a maximum force of 9.4 N

    Doctor of Philosophy

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    dissertationClosed-loop control of wireless capsule endoscopes is an active area of research because it would drastically improve screening of the gastrointestinal tract. Traditional endoscopic procedures are unable to view the entire gastrointestinal tract and current commercial wireless capsule endoscopes are limited in their effectiveness due to their passive nature. This dissertation advances the field of active capsule endoscopy by developing methods to localize the full six-degree-of-freedom (6-DOF) pose of a screw-type magnetic capsule while it is being propelled through a lumen (such as the small intestines) using an external rotating magnetic dipole. The same external magnetic dipole is utilized for both propulsion and localization. Hardware was designed and constructed to enable testing of the magnetic localization and propulsion methods, including a robotic end-effector used as the external actuator magnet, and a prototype capsule embedded with Hall-effect sensors. Due to the use of a rotating magnetic field for propulsion, at any given time, the capsule can be in one of three regimes: synchronously rotating with the applied field, in "step-out" where it is free to move but the external field is rotating too quickly for the capsule to remain synchronously rotating, or completely stationary. We show that it is only necessary to distinguish whether or not the capsule is synchronously rotating (i.e., a single localization method can be used for a capsule in either the step-out or stationary regimes). Two magnetic localization methods are developed. The first uses nonlinear least squares to estimate the capsule's pose when it has no (or approximately no) net motion (e.g., to find the initial capsule pose or when it is stuck in an intestinal fold). The second method estimates the 6-DOF capsule pose as it synchronously rotates with the applied magnetic field using a square-root variant of the Unscented Kalman filter. A simple process model is adopted that restricts the capsule's movement to translation along and rotation about its principle axis. The capsule is actively propelled forward or backward, but it is not actively steered, rather, steering is provided by the lumen. The propulsion parameters that transform magnetic force and torque to the capsule's spatial velocity and angular velocity are estimated with an additional square-root Unscented Kalman filter to enable the capsule to navigate heterogeneous environments such as the small intestines. An optimized localization-propulsion system is described using the two localization algorithms and prior work in screw-type magnetic capsule propulsion with a single rotating dipole field. The capsule's regime is determined and the corresponding localization method is employed. Based on the capsule's estimated pose and the current estimates of its propulsion parameters, the actuator magnet's pose relative to the capsule is optimized to maximize the capsule's forward propulsion. Using this system, our prototype magnetic capsule successfully completed U-shaped and S-shaped trajectories in fresh bovine intestines with an average forward velocity of 5.5mm/s and 3.5 mm/s, respectively. At this rate it would take approximately 18-30 minutes to traverse the 6 meters of a typical human small intestine

    Vision-based Testbeds For Control System Applicaitons

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    In the field of control systems, testbeds are a pivotal step in the validation and improvement of new algorithms for different applications. They provide a safe, controlled environment typically having a significantly lower cost of failure than the final application. Vision systems provide nonintrusive methods of measurement that can be easily implemented for various setups and applications. This work presents methods for modeling, removing distortion, calibrating, and rectifying single and two camera systems, as well as, two very different applications of vision-based control system testbeds: deflection control of shape memory polymers and trajectory planning for mobile robots. First, a testbed for the modeling and control of shape memory polymers (SMP) is designed. Red-green-blue (RGB) thresholding is used to assist in the webcam-based, 3D reconstruction of points of interest. A PID based controller is designed and shown to work with SMP samples, while state space models were identified from step input responses. Models were used to develop a linear quadratic regulator that is shown to work in simulation. Also, a simple to use graphical interface is designed for fast and simple testing of a series of samples. Second a robot testbed is designed to test new trajectory planning algorithms. A templatebased predictive search algorithm is investigated to process the images obtained through a lowcost webcam vision system, which is used to monitor the testbed environment. Also a userfriendly graphical interface is developed such that the functionalities of the webcam, robots, and optimizations are automated. The testbeds are used to demonstrate a wavefront-enhanced, Bspline augmented virtual motion camouflage algorithm for single or multiple robots to navigate through an obstacle dense and changing environment, while considering inter-vehicle conflicts, iv obstacle avoidance, nonlinear dynamics, and different constraints. In addition, it is expected that this testbed can be used to test different vehicle motion planning and control algorithms

    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
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