Novel miniature MRI-compatible fiber-optic force sensor for cardiac catherization procedures

Proceedings of: 2010 IEEE International Conference on Robotics and Automation (ICRA'10), May 3-8, 2010, Anchorage (Alaska, USA)This paper presents the prototype design and development of a miniature MR-compatible fiber optic force sensor suitable for the detection of force during MR-guided cardiac catheterization. The working principle is based on light intensity modulation where a fiber optic cable interrogates a reflective surface at a predefined distance inside a catheter shaft. When a force is applied to the tip of the catheter, a force sensitive structure varies the distance and the orientation of the reflective surface with reference to the optical fiber. The visual feedback from the MRI scanner can be used to determine whether or not the catheter tip is normal or tangential to the tissue surface. In both cases the light is modulated accordingly and the axial or lateral force can be estimated. The sensor exhibits adequate linear response, having a good working range, very good resolution and good sensitivity in both axial and lateral force directions. In addition, the use of low-cost and MR-compatible materials for its development makes the sensor safe for use inside MRI environments.European Community's Seventh Framework Progra

Modeling of Soft Fiber-Reinforced Bending Actuators

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Soft Fiber-Reinforced Pneumatic Actuator Design and Fabrication: Towards Robust, Soft Robotic Systems

© Springer Nature Switzerland AG 2019. Soft robotics is a rapidly evolving, young research area. So far there are no well-established design standards nor fabrication procedures for soft robots. A number of research groups are working on soft robotics solutions independently and we can observe a range of designs realized in different ways. These soft robots are based on various actuation principles, are driven with various actuation media, and offer various actuation properties. Still, most of them require lots of manual effort and high manual fabrication skills from the person manufacturing these kinds of robots. A significant share of the proposed designs suffers from some imperfections that could be improved by simple design changes. In this work, we propose a number of design and fabrication rules for improving the performance and fabrication complexity of soft fiber-reinforced pneumatic actuators. The proposed design approach focuses on a circular geometry for the pressure chambers and applying a dense, fiber-based reinforcement. Such an approach allows for a more linear actuator response and reduced wear of the actuators, when compared to previous approaches. The proposed manufacturing procedure introduces the application of the reinforcement before the fabrication of the actuator body, significantly reducing the required fabrication effort and providing more consistent and more reliable results

Contact force sensor based on microfiber Bragg grating

We demonstrate a miniature contact force sensor based on a 30-µm diameter microfiber Bragg grating packaged with a conforming elastomer material features extremely high sensitivity up to 0.8-mN to contract force.Department of Electrical EngineeringDepartment of Electronic and Information Engineerin

Data-Driven Bending Angle Prediction of Soft Pneumatic Actuators with Embedded Flex Sensors

This paper was presented at MECHATRONICS 2016: 7th IFAC Symposium on Mechatronic Systems & 15th Mechatronics Forum International Conference Loughborough University 5th - 8th September 2016.In this paper, resistive flex sensors have been embedded at the strain limiting layer of soft pneumatic actuators, in order to provide sensory feedback that can be utilised in predicting their bending angle during actuation. An experimental setup was prepared to test the soft actuators under controllable operating conditions, record the resulting sensory feedback, and synchronise this with the actual bending angles measured using a developed image processing program. Regression analysis and neural networks are two data-driven modelling techniques that were implemented and compared in this study, to evaluate their ability in predicting the bending angle response of the tested soft actuators at different input pressures and testing orientations. This serves as a step towards controlling this class of soft bending actuators, using data-driven empirical models that lifts the need for complex analytical modelling and material characterisation. The aim is to ultimately create a more controllable version of this class of soft pneumatic actuators with embedded sensing capabilities, to act as compliant soft gripper fingers that can be used in applications requiring both a ‘soft touch’ as well as more controllable object manipulation

Bending angle prediction and control of soft pneumatic actuators with embedded flex sensors: a data-driven approach

In this paper, a purely data-driven modelling approach is presented for predicting and controlling the free bending angle response of a typical soft pneumatic actuator (SPA), embedded with a resistive flex sensor. An experimental setup was constructed to test the SPA at different input pressure values and orientations, while recording the resulting feedback from the embedded flex sensor and on-board pressure sensor. A calibrated high speed camera captures image frames during the actuation, which are then analysed using an image processing program to calculate the actual bending angle and synchronise it with the recorded sensory feedback. Empirical models were derived based on the generated experimental data using two common data-driven modelling techniques; regression analysis and artificial neural networks. Both techniques were validated using a new dataset at untrained operating conditions to evaluate their prediction accuracy. Furthermore, the derived empirical model was used as part of a closed-loop PID controller to estimate and control the bending angle of the tested SPA based on the real-time sensory feedback generated. The tuned PID controller allowed the bending SPA to accurately follow stepped and sinusoidal reference signals, even in the presence of pressure leaks in the pneumatic supply. This work demonstrates how purely data-driven models can be effectively used in controlling the bending of SPAs under different operating conditions, avoiding the need for complex analytical modelling and material characterisation. Ultimately, the aim is to create more controllable soft grippers based on such SPAs with embedded sensing capabilities, to be used in applications requiring both a ‘soft touch’ as well as a more controllable object manipulation

Directly Printable Flexible Strain Sensors for Bending and Contact Feedback of Soft Actuators

This paper presents a fully printable sensorized bending actuator that can be calibrated to provide reliable bending feedback and simple contact detection. A soft bending actuator following a pleated morphology, as well as a flexible resistive strain sensor, were directly 3D printed using easily accessible FDM printer hardware with a dual-extrusion tool head. The flexible sensor was directly welded to the bending actuator’s body and systematically tested to characterize and evaluate its response under variable input pressure. A signal conditioning circuit was developed to enhance the quality of the sensory feedback, and flexible conductive threads were used for wiring. The sensorized actuator’s response was then calibrated using a vision system to convert the sensory readings to real bending angle values. The empirical relationship was derived using linear regression and validated at untrained input conditions to evaluate its accuracy. Furthermore, the sensorized actuator was tested in a constrained setup that prevents bending, to evaluate the potential of using the same sensor for simple contact detection by comparing the constrained and free-bending responses at the same input pressures. The results of this work demonstrated how a dual-extrusion FDM printing process can be tuned to directly print highly customizable flexible strain sensors that were able to provide reliable bending feedback and basic contact detection. The addition of such sensing capability to bending actuators enhances their functionality and reliability for applications such as controlled soft grasping, flexible wearables, and haptic devices

Design and validation of exoskeleton actuated by soft modules towards neurorehabilitation - vision-based control for precise reaching motion of upper limb

We demonstrated the design, production, and functional properties of the Exoskeleton Actuated by the Soft Modules (EAsoftM). Integrating the 3D printed exoskeleton with passive joints to compensate gravity and with active joints to rotate the shoulder and elbow joints resulted in ultra-light system that could assist planar reaching motion by using the vision-based control law. The EAsoftM can support the reaching motion with compliance realised by the soft materials and pneumatic actuation. In addition, the vision-based control law has been proposed for the precise control over the target reaching motion within the millimeter scale. % Aiming at rehabilitation exercise for individuals, typically soft actuators have been developed for relatively small motions, such as grasping motion, and one of the challenges has been to extend their use for a wider range reaching motion. The proposed EAsoftM presented one possible solution for this challenge by transmitting the torque effectively along the anatomically aligned with a human body exoskeleton. % The proposed integrated systems will be an ideal solution for neurorehabilitation where affordable wearable and portable systems are required to be customised for individuals with specific motor impairments