428 research outputs found
Finite Element Modelling of Soft Tissue Rolling Indentation
No full textWe describe a finite-element (FE) model for simulating wheel-rolling tissue deformations using a rolling FE model (RFEM). A wheeled probe performing rolling tissue indentation has proven to be a promising approach for compensating for the loss of haptic and tactile feedback experienced during robotic-assisted minimally invasive surgery (H. Liu, D. P. Noonan, B. J. Challacombe, P. Dasgupta, L. D. Seneviratne, and K. Althoefer, Rolling mechanical imaging for tissue abnormality localization during minimally invasive surgery, IEEE Trans. Biomed. Eng., vol. 57, no. 2, pp. 404-414, Feb. 2010; K. Sangpradit, H. Liu, L. Seneviratne, and K. Althoefer, Tissue identification using inverse finite element analysis of rolling indentation, in Proc. IEEE Int. Conf. Robot. Autom. , Kobe, Japan, 2009, pp. 1250-1255; H. Liu, D. Noonan, K. Althoefer, and L. Seneviratne, The rolling approach for soft tissue modeling and mechanical imaging during robot-assisted minimally invasive surgery, in Proc. IEEE Int. Conf. Robot. Autom., May 2008, pp. 845-850; H. Liu, P. Puangmali, D. Zbyszewski, O. Elhage, P. Dasgupta, J. S. Dai, L. Seneviratne, and K. Althoefer, An indentation depth-force sensing wheeled probe for abnormality identification during minimally invasive surgery, Proc. Inst. Mech. Eng., H, vol. 224, no. 6, pp. 751-63, 2010; D. Noonan, H. Liu, Y. Zweiri, K. Althoefer, and L. Seneviratne, A dual-function wheeled probe for tissue viscoelastic property identification during minimally invasive surgery, in Proc. IEEE Int. Conf. Robot. Autom. , 2008, pp. 26292634; H. Liu, J. Li, Q. I. Poon, L. D. Seneviratne, and K. Althoefer, Miniaturized force indentation-depth sensor for tissue abnormality identification, IEEE Int. Conf. Robot. Autom., May 2010, pp. 3654-3659). A sound understanding of wheel-tissue rolling interaction dynamics will facilitate the evaluation of signals from rolling indentation. In this paper, we model the dynamic interactions between a wheeled probe and a soft tissue sample using the ABAQUS FE software package. The aim of this work is to more precisely locate abnormalities within soft tissue organs using RFEM and hence aid surgeons to improve diagnostic ability. The soft tissue is modeled as a nonlinear hyperelastic material with geometrical nonlinearity. The proposed RFEM was validated on a silicone phantom and a porcine kidney sample. The results show that the proposed method can predict the wheel - tissue interaction forces of rolling indentation with good accuracy and can also accurately identify the location and depth of simulated tumor
Modelling of a soft sensor for exteroception and proprioception in a pneumatically actuated soft robot
No full text© Springer Nature Switzerland AG 2019. Soft sensors are crucial to enable feedback in soft robots. Soft capacitive sensing is a reliable technology that can be embedded into soft pneumatic robots for obtaining proprioceptive and exteroceptive feedback. In this paper, we model a soft capacitive sensor that measures both the actuated state as well as applied external forces. We develop a Finite Element Model using a multiphysics software (COMSOL®). Using this model, we investigate the change in capacitance with the application of external force, for a range of different internal pressures and strains. We hope this study is helpful in understanding the coupling of internal inputs and external stimuli on the feedback obtained from the sensors and help us design better sensory systems for soft robots
Design Analysis of a Fabric Based Lightweight Robotic Gripper
No full textThe development of grasping mechanisms for various grasping applications have enabled robots to perform a wide variety of tasks in both industrial as well as domestic applications. Soft robotic grippers have been very useful in grasping applications with an added advantage of simpler control mechanisms as compared to rigid grippers. In this paper, a two fingered gripper inspired by the fingers of a human hand is introduced. The gripper is made from fabrics and, hence, compliant, lightweight, completely foldable and boasts a high payload capability. The mechanical design of the gripper is optimized through experiments, a maximum bending angle of 180° is achieved. We demonstrate grasping of a variety of objects using the new gripper
Payload capabilities and operational limits of eversion robots
No full textRecent progress in soft robotics has seen new types of actuation mechanisms based on apical extension which allows robots to grow to unprecedented lengths. Eversion robots are a type of robots based on the principle of apical extension offering excellent maneuverability and ease of control allowing users to conduct tasks from a distance. Mechanical modelling of these robotic structures is very important for understanding their operational capabilities. In this paper, we model the eversion robot as a thin-walled cylindrical beam inflated with air pressure, using Timoshenko beam theory considering rotational and shear effects. We examine the various failure modes of the eversion robots such as yielding, buckling instability and lateral collapse, and study the payloads and operational limits of these robots in axial and lateral loading conditions. Surface maps showing the operational boundaries for different combinations of the geometrical parameters are presented. This work provides insights into the design of eversion robots and can pave the way towards eversion robots with high payload capabilities that can act from long distances
Experimental Data
No full textExperimental data used in the following research paper, which presents a minimally invasive wearable muscle sensing device consisting of jogging leggings, with embroidered surface EMG electrodes. Muscle activity from the quadriceps group is collected during running trials on multiple surfaces. R. B. Ribas Manero, J. Grewal, B. Michael, A. Shafti, K. Althoefer, J. Ll. Ribas Fernandez, M. J. Howard. "Wearable Embroidered Muscle Activity Sensing Device for the Human Upper Leg." EMBC (2016), In Press.<br
Highly Manoeuvrable Eversion Robot Based on Fusion of Function with Structure
No full textDespite their soft and compliant bodies, most of today’s soft robots have limitations when it comes to elongation or extension of their main structure. In contrast to this, a new type of soft robot called the eversion robot can grow longitudinally, exploiting the principle of eversion. Eversion robots can squeeze through narrow openings, giving the possibility to access places that are inaccessible by conventional robots. The main drawback of these types of robots is their limited bending capability due to the tendency to move along a straight line. In this paper, we propose a novel way to fuse bending actuation with the robot’s structure. We devise an eversion robot whose body forms both the central chamber that acts as the backbone as well as the actuators that cause bending and manoeuvre the manipulator. The proposed technique shows a significantly improved bending capability compared to externally attaching actuators to an eversion robot showing a 133% improvement in bending angle. Due to the increased manoeuvrability, the proposed solution is a step towards the employment of eversion robots in remote and difficult-to-access environments
Magnetic-Field-Inspired Navigation for Robots in Complex and Unknown Environments
No full textOver the course of the past decade, we have witnessed a huge expansion in robotic applications, most notably from well-defined industrial environments into considerably more complex environments. The obstacles that these environments often contain present robotics with a new challenge - to equip robots with a real-time capability of avoiding them. In this paper, we propose a magnetic-field-inspired navigation method that significantly has several advantages over alternative systems. Most importantly, 1) it guarantees obstacle avoidance for both convex and non-convex obstacles, 2) goal convergence is still guaranteed for point-like robots in environments with convex obstacles and non-maze concave obstacles, 3) no prior knowledge of the environment, such as the position and geometry of the obstacles, is needed, 4) it only requires temporally and spatially local environmental sensor information, and 5) it can be implemented on a wide range of robotic platforms in both 2D and 3D environments. The proposed navigation algorithm is validated in simulation scenarios as well as through experimentation. The results demonstrate that robotic platforms, ranging from planar point-like robots to robot arm structures such as the Baxter robot, can successfully navigate toward desired targets within an obstacle-laden environment. Copyright © 2022 Ataka, Lam and Althoefer
Model-based Pose Control of Inflatable Eversion Robot with Variable Stiffness
No full textPlant-inspired inflatable eversion robots with their tip growing behaviour have recently emerged. Because they extend from the tip, eversion robots are particularly suitable for applications that require reaching into remote places through narrow openings. Besides, they can vary their structural stiffness. Despite these essential properties which make the eversion robot a promising candidate for applications involving cluttered environments and tight spaces, controlling their motion especially laterally has not been investigated in depth. In this letter, we present a new approach based on model-based kinematics to control the eversion robot's tip position and orientation. Our control approach is based on Euler-Bernoulli beam theory which takes into account the effect of the internal inflation pressure to model each robot bending segment for various conditions of structural stiffness. We determined the parameters of our bending model by performing a least-square technique based on the pressure-bending data acquired from an experimental study. The model is then used to develop a pose controller for the tip of our eversion robot. Experimental results show that the proposed control strategy is capable of guiding the tip of the eversion robot to reach a desired position and orientation whilst varying its structural stiffness
A Kalman Filter-Integrated Optical Flow Method for Velocity Sensing of Mobile Robots
No full textThis paper presents a Kalman filter (KF)-integrated optical flow method to measure the velocity of mobile robots using a downward-looking camera. Tests conducted earlier by the authors have shown that currently available differential optical flow methods (X. Song, L. D. Seneviratne, K. Althoefer, and Z. Song, "Vision-based velocity estimation for unmanned ground vehicles," Int. J. Inf. Acquis., vol. 4, no. 4, pp. 303-315, 2007) require large image overlap for accurate velocity estimation. This constraint significantly limits the usefulness of this approach in practical applications. To overcome the problem of dealing with large image displacements, a KF is incorporated to efficiently predict the image transformations. Reducing the feature search area, the KF enables the differential optical flow method to rapidly converge and give accurate velocity estimates. The proposed method has been validated on a linear test rig under laboratory conditions and on a mobile platform in an outdoor field. Test results show good performance of the proposed method in velocity measurements with large image displacements. With this improvement, the required image overlap for feature tracking can be reduced approximately from 80% to 20%, resulting in a fourfold increase of the maximum measurable velocity of the mobile platform. The proposed method has good potential in velocity sensing for mobile robots, particularly in cases, where GPS and inertial measurement unit fail or are unavailable
Representation of Distributed Haptic Feedback Given via Vibro-tactile Actuator Arrays
No full textThere are many studies to suggest that the human motor system adaptively combines motor primitives to control limb movements. However, little is known about whether the somatosensory system too uses a similar strategy to efficiently represent haptic experiences. Since it has been shown that humans learn movements through flexible combination of primitives that can be modeled using Gaussian-like functions, we try to explore whether human brain uses similar primitives to represent haptic memory too. We tested whether haptic memory is localized and magnitude specific along the arm. Therefore, experiments were conducted to understand how humans trained in primitive haptic patterns given using a wearable sleeve can recognize their shifts and linear combinations. A wearable sleeve was used that consisted of seven vibro-actuators to convey the primitive patterns. We found that (1) subjects find it easier to recognize uni-modal haptic templates. When they are given bi-modal patterns, subjects tend to generalize them to uni-modal patterns; (2) haptic memory is location specific. When the same template is shifted along the arm, the original template interferes with the shifted pattern. (3) subjects can recognize linear combinations of previously trained haptic templates. In addition to the prototype presented in Chapter 14, this chapter provides guidelines to design haptic feedback system for STIFF-FLOP continuum manipulator. The scenarios can include separation of force and torque into different distributed haptic feedback templates, and recognition of tissue contact forces at multiple points along the arm using optimally designed feedback templates using vibro-tactile actuator array
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