Imperial College London

Dr Thrishantha Nanayakkara

Faculty of EngineeringDyson School of Design Engineering

Professor in Robotics
 
 
 
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Contact

 

+44 (0)20 7594 0965t.nanayakkara Website CV

 
 
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Location

 

RCS1 M229Dyson BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

142 results found

He L, Maiolino P, Leong F, Lalitharatne T, Lusignan SD, Ghajari M, Iida F, Nanayakkara Tet al., 2022, Robotic simulators for tissue examination training with multimodal sensory feedback, IEEE Reviews in Biomedical Engineering, ISSN: 1941-1189

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators.

Journal article

Yu Z, Sadati SMH, Hauser H, Childs PRN, Nanayakkara Tet al., 2022, A Semi-Supervised Reservoir Computing System Based on Tapered Whisker for Mobile Robot Terrain Identification and Roughness Estimation, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 7, Pages: 5655-5662, ISSN: 2377-3766

Journal article

Yu Z, Perera S, Hauser H, Childs P, Nanayakkara Tet al., 2022, A tapered whisker-based physical reservoir computing system for mobile robot terrain identification in unstructured environments, IEEE Robotics and Automation Letters, Vol: 7, Pages: 3608-3615, ISSN: 2377-3766

In this letter, we present for the first time the use of tapered whisker-based reservoir computing (TWRC) system mounted on a mobile robot for terrain classification and roughness estimation of unknown terrain.Hall effect sensors captured the oscillations at different locations along a tapered spring that served as a reservoir to map time-domain vibrations signals caused by the interaction perturbations from the ground to frequency domain features directly. Three hall sensors are used to measure the whisker reservoir outputs and these temporal signals could be processed efficiently by the proposed TWRC system which can provide morphological computation power for data processing and reduce the model training cost compared to the convolutional neural network (CNN) approaches.To predict the unknown terrain properties, an extended TWRC method including a novel detector is proposed based on the Mahalanobis distance in the Eigen space, which has been experimentally demonstrated to be feasible and sufficiently accurate.We achieved a prediction success rate of 94.3\% for six terrain surface classification experiments and 88.7\% for roughness estimation of the unknown terrain surface.

Journal article

Ge Y, Nanayakkara T, Dulantha Lalitharatne T, 2022, Origami inspired design for capsule endoscope to retrograde using intestinal peristalsis, IEEE Robotics and Automation Letters, Vol: 7, Pages: 5429-5435, ISSN: 2377-3766

Capsule endoscopy has gained a lot of attentionin the medical field in the recent past as an effective way ofinvestigating unusual symptoms experienced in places such asesophagus, stomach, small intestine and colon. However, motioncontrol of the capsule endoscope is challenging and often requiresa power source and miniature actuators. To address these issues,we present a novel origami inspired structure as an attachmentto the capsule endoscope. The proposed origami structure utilizesthe wave generated by peristalsis of the intestine to move itforward and backward. When the origami structure is folded, thecapsule endoscope is propelled forward by intestinal peristalsis.When the origami structure is unfolded, the intestinal peristalsissqueezes the origami structure to drive the capsule endoscope tomove in the opposite direction. Therefore, folding and unfoldingof the proposed origami structure would allow to control themovement direction of the capsule endoscope. In this paper, wepresent the design, simulations and experimental validation ofthe proposed origami structure.

Journal article

He L, Herzig N, Nanayakkara T, Maiolino Pet al., 2022, 3D-printed soft sensors for adaptive sensing with online and offline tunable-stiffness, Soft Robotics, ISSN: 2169-5172

he stiffness of a soft robot with structural cavities can be regulated by controlling the pressure of a fluid to render predictable changes in mechanical properties. When the soft robot interacts with the environment, the mediating fluid can also be considered an inherent information pathway for sensing. This approach to using structural tuning to improve the efficacy of a sensing task with specific states has not yet been well studied. A tunable stiffness soft sensor also renders task-relevant contact dynamics in soft robotic manipulation tasks. This paper proposes a type of adaptive soft sensor that can be directly 3D printed and controlled using pneumatic pressure. The tunability of such a sensor helps to adjust the sensing characteristics to better capturing specific tactile features, demonstrated by detecting texture with different frequencies. We present the design, modelling, Finite Element Simulation, and experimental characterisation of a single unit of such a tunable stiffness sensor. How the sensing characteristics are affected by adjusting its stiffness is studied in depth. In additional to the tunability, the results show such type of adaptive sensors exhibit good sensitivity (up to 2.6 [KPa/N]), high sensor repeatability (average std < 0.008 [KPa/N]), low hysteresis (< 6%), and good manufacturing repeatability (average std = 0.0662[KPa/N]).

Journal article

Tan Y, Rerolle S, Lalitharathne TD, Zalk NV, Jack R, Nanayakkara Tet al., 2022, Simulating dynamic facial expressions of pain from visuo-haptic interactions with a robotic patient, Scientific Reports, Vol: 12, ISSN: 2045-2322

Medical training simulators can provide a safe and controlled environment for medical students to practice their physical examination skills. An important source of information for physicians is the visual feedback of involuntary pain facial expressions in response to physical palpation on an affected area of a patient. However, most existing robotic medical training simulators that can capture physical examination behaviours in real-time cannot display facial expressions and comprise a limited range of patient identities in terms of ethnicity and gender. Together, these limitations restrict the utility of medical training simulators because they do not provide medical students with a representative sample of pain facial expressions and face identities, which could result in biased practices. Further, these limitations restrict the utility of such medical simulators to detect and correct early signs of bias in medical training. Here, for the first time, we present a robotic system that can simulate facial expressions of pain in response to palpations, displayed on a range of patient face identities. We use the unique approach of modelling dynamic pain facial expressions using a data-driven perception-based psychophysical method combined with the visuo-haptic inputs of users performing palpations on a robot medical simulator. Specifically, participants performed palpation actions on the abdomen phantom of a simulated patient, which triggered the real-time display of six pain-related facial Action Units (AUs) on a robotic face (MorphFace), each controlled by two pseudo randomly generated transient parameters: rate of change β and activation delay τ. Participants then rated the appropriateness of the facial expression displayed in response to their palpations on a 4-point scale from “strongly disagree” to “strongly agree”. Each participant (n=16, 4 Asian females, 4 Asian males, 4 White females and 4 White males) performed 200 palpation

Journal article

Berkovic A, Laganier C, Chappell D, Nanayakkara T, Kormushev P, Bello F, Rojas Net al., 2022, A multi-modal haptic armband for finger-level sensory feedback from a prosthetic hand, EuroHaptics

Conference paper

Nanayakkara T, Barfoot T, Howard T, 2021, Robotics: Science and Systems (RSS) 2020, INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, Vol: 40, Pages: 1329-1330, ISSN: 0278-3649

Journal article

Carboni G, Nanayakkara T, Takagi A, Burdet Eet al., 2021, Adapting the visuo-haptic perception through muscle coactivation, SCIENTIFIC REPORTS, Vol: 11, ISSN: 2045-2322

Journal article

He L, Leong F, Dulantha Lalitharatne T, De Lusignan S, Nanayakkara Tet al., 2021, A haptic mouse design with stiffening muscle layer for simulating guarding in abdominal palpation training, IEEE International Conference on Robotics and Automation (ICRA 2021), Publisher: IEEE, Pages: 12588-12594, ISSN: 2152-4092

A patient would contract surface muscles as areaction called muscle guarding when experiencing discomfortand pain during physical palpation. This reaction carries impor-tant information about an affected location. Training physiciansto regulate palpation forces to elicit just enough muscle tensionis a challenge using real patients. Tunable stiffness mechanismsenabled by soft robotics can be effectively integrated intomedical simulator designs for effective clinical education. Inthis paper, we propose a controllable stiffness muscle layer tosimulate guarding for abdominal palpation training. Designswith soft, fine, and rigid granular jamming, stretchable andnon-stretchable layer jamming mechanisms were tested andevaluated as methods to create controllable stiffness muscle.User studies have been carried out on10naive participants todifferentiate the tense and relaxed abdomen with the proposedjamming mechanisms. Muscle samples made of ground coffee(fine granular jamming) and latex layers (stretchable layerjamming) show good usability in simulating abdomen withdifferent stiffness with at least 75% of the user data exhibitsmore than70%of decision accuracy for both tested palpationgestures (single finger and multiple fingers) after short pre-training.

Conference paper

Costi L, Scimeca L, Maiolino P, Lalitharatne TD, Nanayakkara T, Hashem R, Iida Fet al., 2021, Comparative analysis of model-based predictive shared control for delayed operation in object reaching and recognition tasks with tactile sensing, Frontiers in Robotics and AI, Vol: 8, ISSN: 2296-9144

Communication delay represents a fundamental challenge in telerobotics: on one hand, it compromises the stability of teleoperated robots, on the other hand, it decreases the user’s awareness of the designated task. In scientific literature, such a problem has been addressed both with statistical models and neural networks (NN) to perform sensor prediction, while keeping the user in full control of the robot’s motion. We propose shared control as a tool to compensate and mitigate the effects of communication delay. Shared control has been proven to enhance precision and speed in reaching and manipulation tasks, especially in the medical and surgical fields. We analyse the effects of added delay and propose a unilateral teleoperated leader-follower architecture that both implements a predictive system and shared control, in a 1-dimensional reaching and recognition task with haptic sensing. We propose four different control modalities of increasing autonomy: non-predictive human control (HC), predictive human control (PHC), (shared) predictive human-robot control (PHRC), and predictive robot control (PRC). When analyzing how the added delay affects the subjects’ performance, the results show that the HC is very sensitive to the delay: users are not able to stop at the desired position and trajectories exhibit wide oscillations. The degree of autonomy introduced is shown to be effective in decreasing the total time requested to accomplish the task. Furthermore, we provide a deep analysis of environmental interaction forces and performed trajectories. Overall, the shared control modality, PHRC, represents a good trade-off, having peak performance in accuracy and task time, a good reaching speed, and a moderate contact with the object of interest.

Journal article

Scimeca L, Hughes J, He L, Nanayakkara T, Iida Fet al., 2021, Action augmentation of tactile perception for soft-body palpation, Soft Robotics, Vol: 9, ISSN: 2169-5180

Medical palpation is a diagnostic technique in which physicians use the sense of touch to manipulate the soft human tissue. This can be to enable the diagnosis of possibly life-threatening conditions, such as cancer. Palpation is still poorly understood because of the complex interaction dynamics between the practitioners’ hands and the soft human body. To understand this complex soft body interactions, we explore robotic palpation for the purpose of diagnosing the presence of abnormal inclusions, or tumours. Using a Bayesian framework for training and classification, we show that the for the exploration of soft bodies requires complex, multi-axis, palpation trajectories. We also find that this probabilistic approach is capable of rapidly searching the large action space of the robot. This work progresses ‘robotic’ palpation, and provides frameworks for understanding and exploiting soft body interactions.

Journal article

He L, Herzig N, Lusignan SD, Scimeca L, Maiolino P, Iida F, Nanayakkara Tet al., 2021, An Abdominal phantom with tunable stiffness nodules and force sensing capability for palpation training, IEEE Transactions on Robotics, Vol: 37, Pages: 1051-1064, ISSN: 1552-3098

Robotic phantoms enable advanced physical examination training before using human patients. In this article, we present an abdominal phantom for palpation training with controllable stiffness liver nodules that can also sense palpation forces. The coupled sensing and actuation approach is achieved by pneumatic control of positive-granular jammed nodules for tunable stiffness. Soft sensing is done using the variation of internal pressure of the nodules under external forces. This article makes original contributions to extend the linear region of the neo-Hookean characteristic of the mechanical behavior of the nodules by 140&#x0025; compared to no-jamming conditions and to propose a method using the organ level controllable nodules as sensors to estimate palpation position and force with a root-mean-square error of 4&#x0025; and 6.5&#x0025;, respectively. Compared to conventional soft sensors, the method allows the phantom to sense with no interference to the simulated physiological conditions when providing quantified feedback to trainees, and to enable training following current bare-hand examination protocols without the need to wear data gloves to collect data.

Journal article

Yu Z, SMHadi S, Hasitha W, Childs P, Nanayakkara Tet al., 2021, A method to use reservoir computing in a whisker sensor for terrain identification by mobile robots, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems

This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that the whisker vibrations will have a dominant frequency at the vertical perturbation frequency of the mobile robot sandwiched by two other less dominant but distinct frequency components. These frequency components may come from bifurcation of vibration frequency due to nonlinear interaction dynamics at steady state. Experimental results also exhibit distinct dominant frequency components unique to the speed of the robot and the terrain roughness. This nonlinear dynamic feature is used in a deep multi-layer perceptron neural network to classify terrains. We achieved 85.6% prediction success rate for seven flat terrain surfaces with different textures.Index Terms— Robotic whiskers, Surface identification, multi-layer perceptron, Modal analysis.

Conference paper

He L, Tan X, Suzumori K, Nanayakkara Tet al., 2021, A method to 3D print a programmable continuum actuator with single material using internal constraint, Sensors and Actuators A: Physical, Vol: 324, ISSN: 0924-4247

Soft continuum robots require differential control of channel pressure across several modules to trace 3D trajectories at the tip. For current designs of such actuators, sheathing is required to prevent radial expansion when the chambers are pressurized. With the recent development of soft materials additive manufacturing, 3D printing has become a promising fabrication method for soft continuum robots. However, most current designs for continuum actuators are based on molding, which are not designed for 3D printing. This paper proposes an internal constraint-based soft continuum actuator for single material 3D printing, with tunable design parameters to render pre-defined motions. The internal constraint method maximizes the superiority of the rapid prototyping solution in terms of customizing the soft continuum actuators with high fabrication speed and design freedom. The internal constraints come in the form of internal beam elements that not only limit the undesired radial expansion (up to ∼14% of conventional design) but also allows the actuator to be pressurized at a higher driving pressure (up to ∼160%) and higher maximum bending angle (up to ∼320%) compared to conventional no-beam design. By tuning the design parameter q (determined by the number of constraint beams n per radial cross-section and the number of such sections k along the axial direction), we can render the actuator to the desired movement under specific driving pressure p. We show numerical simulation and hardware experiment results for a soft actuator to achieve specified bending and twisting motions following this design approach.

Journal article

Lalitharatne SWH, Tan Y, He L, Leong F, Van Zalk N, De Lusignan S, Iida F, Nanayakkara Tet al., 2021, MorphFace: a hybrid morphable face for a robopatient, IEEE Robotics and Automation Letters, Vol: 6, Pages: 643-650, ISSN: 2377-3766

Physicians use pain expressions shown in a patient’sface to regulate their palpation methods during physical examination.Training to interpret patients’ facial expressions withdifferent genders and ethnicities still remains a challenge, takingnovices a long time to learn through experience. This paperpresents MorphFace: a controllable 3D physical-virtual hybridface to represent pain expressions of patients from differentethnicity-gender backgrounds. It is also an intermediate stepto expose trainee physicians to the gender and ethnic diversityof patients. We extracted four principal components from theChicago Face Database to design a four degrees of freedom(DoF) physical face controlled via tendons to span 85% offacial variations among gender and ethnicity. Details such as skincolour, skin texture, and facial expressions are synthesized by avirtual model and projected onto the 3D physical face via a frontmountedLED projector to obtain a hybrid controllable patientface simulator. A user study revealed that certain differences inethnicity between the observer and the MorphFace lead to differentperceived pain intensity for the same pain level rendered bythe MorphFace. This highlights the value of having MorphFace asa controllable hybrid simulator to quantify perceptual differencesduring physician training.

Journal article

Hamid E, Herzig N, Guaman SA-A, Nanayakkara Tet al., 2021, A state-dependent damping method to reduce collision force and its variability, IEEE Robotics and Automation Letters, Vol: 6, Pages: 3025-3032, ISSN: 2377-3766

This letter investigates the effect of biologically inspired angle-dependent damping profile in a robotic joint primarily on the magnitude and the variability of the peak collision force. Joints such as the knee that experience collision forces are known to have an angle-dependent damping profile. In this letter, we have quantified and compared three damping profiles. Our numerical and experimental results show that the proposed hyperbolic angle-dependent damping profile can minimize both the magnitude and the variability of the peak collision force (average magnitude and variability reduction of ≈26% and ≈47% compared to the peak constant damping profile). Very often, the variability of the force across the collision between the robot and the environment cause uncertainty about the state variables of the robotic joint. We show that by increasing the slope of the proposed hyperbolic angle-dependent damping profile we can also reduce the variability and the magnitude of post-collision peak displacement and peak velocity compared to those of constant damping profile. This was achieved while reducing the root mean square of power consumed by the robotic joint.

Journal article

Tan X, Ahmed-Kristensen S, Cao J, Zhu Q, Chen W, Nanayakkara Tet al., 2021, A soft pressure sensor skin to predict contact pressure limit under hand orthosis, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 29, Pages: 536-545, ISSN: 1534-4320

Customized static orthoses in rehabilitation clinics often cause side effects, such as discomfort and skin damage due to excessive local contact pressure. Currently, clinicians adjust orthoses to reduce high contact pressure based on subjective feedback from patients. However, the adjustment is inefficient and prone to variability due to the unknown contact pressure distribution as well as differences in discomfort due to pressure across patients. This paper proposed a new method to predict a threshold of contact pressure (pressure limit) associated with moderate discomfort at each critical spot under hand orthoses. A new pressure sensor skin with 13 sensing units was configured from FEA results of pressure distribution simulated with hand geometry data of six healthy participants. It was used to measure contact pressure under two types of customized orthoses for 40 patients with bone fractures. Their subjective perception of discomfort was also measured using a 6 scores discomfort scale. Based on these data, five critical spots were identified that correspond to high discomfort scores (>1) or high pressure magnitudes (>0.024 MPa). An artificial neural network was trained to predict contact pressure at each critical spot with orthosis type, gender, height, weight, discomfort scores and pressure measurements as input variables. The neural networks show satisfactory prediction accuracy with R 2 values over 0.81 of regression between network outputs and measurements. This new method predicts a set of pressure limits at critical locations under the orthosis that the clinicians can use to make orthosis adjustment decisions.

Journal article

Yu Z, Sadati SMH, Wegiriya H, Childs P, Nanayakkara Tet al., 2021, A Method to use Nonlinear Dynamics in a Whisker Sensor for Terrain Identification by Mobile Robots, IEEE International Conference on Intelligent Robots and Systems, Pages: 8437-8443, ISSN: 2153-0858

This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that the whisker vibrations will have one dominant frequency at the vertical perturbation frequency of the mobile robot and one with distinct frequency components. These frequency components may come from bifurcation of vibration frequency due to nonlinear interaction dynamics at steady state. Experimental results also exhibit distinct dominant frequency components unique to the speed of the robot and the terrain roughness. This nonlinear dynamic feature is used in a deep multi-layer perceptron neural network to classify terrains. We achieved 85.6% prediction success rate for seven flat terrain surfaces with different textures.

Journal article

Sadati H, Naghib E, Shiva A, Michael B, Renson L, Howard M, Rucker C, Althoefer K, Nanayakkara DPT, Zschaler S, Bergeles C, Hauser H, Walker Iet al., 2021, TMTDyn: A Matlab package for modeling and control of hybrid rigid–continuum robots based on discretized lumped system and reduced-order models, International Journal of Robotics Research, Vol: 40, Pages: 296-347, ISSN: 0278-3649

A reliable, accurate, and yet simple dynamic model is important to analyzing, designing, and controlling hybrid rigid–continuum robots. Such models should be fast, as simple as possible, and user-friendly to be widely accepted by the ever-growing robotics research community. In this study, we introduce two new modeling methods for continuum manipulators: a general reduced-order model (ROM) and a discretized model with absolute states and Euler–Bernoulli beam segments (EBA). In addition, a new formulation is presented for a recently introduced discretized model based on Euler–Bernoulli beam segments and relative states (EBR). We implement these models in a Matlab software package, named TMTDyn, to develop a modeling tool for hybrid rigid–continuum systems. The package features a new high-level language (HLL) text-based interface, a CAD-file import module, automatic formation of the system equation of motion (EOM) for different modeling and control tasks, implementing Matlab C-mex functionality for improved performance, and modules for static and linear modal analysis of a hybrid system. The underlying theory and software package are validated for modeling experimental results for (i) dynamics of a continuum appendage, and (ii) general deformation of a fabric sleeve worn by a rigid link pendulum. A comparison shows higher simulation accuracy (8–14% normalized error) and numerical robustness of the ROM model for a system with a small number of states, and computational efficiency of the EBA model with near real-time performances that makes it suitable for large systems. The challenges and necessary modules to further automate the design and analysis of hybrid systems with a large number of states are briefly discussed.

Journal article

Lalitharatne SWH, Tan Y, Leong F, He L, Van Zalk N, De Lusignan S, Iida F, Nanayakkara Tet al., 2020, Facial Expression Rendering in Medical Training Simulators: Current Status and Future Directions, IEEE Access, Vol: 8, Pages: 215874-215891, ISSN: 2169-3536

Recent technological advances in robotic sensing and actuation methods have prompteddevelopment of a range of new medical training simulators with multiple feedback modalities. Learning tointerpret facial expressions of a patient during medical examinations or procedures has been one of the keyfocus areas in medical training. This article reviews facial expression rendering systems in medical trainingsimulators that have been reported to date. Facial expression rendering approaches in other domains are alsosummarized to incorporate the knowledge from those works into developing systems for medical trainingsimulators. Classifications and comparisons of medical training simulators with facial expression renderingare presented, and important design features, merits and limitations are outlined. Medical educators,students and developers are identified as the three key stakeholders involved with these systems and theirconsiderations and needs are presented. Physical-virtual (hybrid) approaches provide multimodal feedback,present accurate facial expression rendering, and can simulate patients of different age, gender and ethnicitygroup; makes it more versatile than virtual and physical systems. The overall findings of this review andproposed future directions are beneficial to researchers interested in initiating or developing such facialexpression rendering systems in medical training simulators.

Journal article

Wegiriya H, Herzig N, Guaman SAA, Sadati H, Nanayakkara Tet al., 2020, A stiffness controllable multimodal whisker sensor follicle for texture comparison, IEEE Sensors Journal, Vol: 20, Pages: 2320-2328, ISSN: 1530-437X

Mammals like rats, who live in dark burrows, heav-ily depend on tactile perception obtained through the vibrissalsystem to move through gaps and to discriminate textures. Theorganization of a mammalian whisker follicle contains multiplesensory receptors and glands strategically organized to capturetactile sensory stimuli of different frequencies. In this paper, weused a controllable stiffness soft robotic follicle to test the hy-pothesis that the multimodal sensory receptors together with thecontrollable stiffness tissues in the whisker follicle form a physicalstructure to maximize tactile information. In our design, the ringsinus and ringwulst of a biological follicle are represented by alinear actuator connected to a stiffness controllable mechanismin-between two different frequency-dependent data capturingmodules. In this paper, we show for the first time the effectof the interplay between the stiffness and the speed of whiskingon maximizing a difference metric for texture classification.

Journal article

Herzig N, He L, Maiolino P, Guaman SAA, Nanayakkara Tet al., 2020, Conditioned haptic perception for 3D localization of nodules in soft tissue palpation with a variable stiffness probe, PLoS One, Vol: 15, ISSN: 1932-6203

This paper provides a solution for fast haptic information gain during soft tissue palpation using a Variable Lever Mechanism (VLM) probe. More specifically, we investigate the impact of stiffness variation of the probe to condition likelihood functions of the kinesthetic force and tactile sensors measurements during a palpation task for two sweeping directions. Using knowledge obtained from past probing trials or Finite Element (FE) simulations, we implemented this likelihood conditioning in an autonomous palpation control strategy. Based on a recursive Bayesian inferencing framework, this new control strategy adapts the sweeping direction and the stiffness of the probe to detect abnormal stiff inclusions in soft tissues. This original control strategy for compliant palpation probes shows a sub-millimeter accuracy for the 3D localization of the nodules in a soft tissue phantom as well as a 100% reliability detecting the existence of nodules in a soft phantom.

Journal article

Lu Q, Liang H, Nanayakkara DPT, Rojas Net al., 2020, Precise in-hand manipulation of soft objects using soft fingertips with tactile sensing and active deformation, IEEE International Conference on Soft Robotics, Publisher: IEEE, Pages: 52-57

While soft fingertips have shown significant development for grasping tasks, its ability to facilitate the manipulation of objects within the hand is still limited. Thanks to elasticity, soft fingertips enhance the ability to grasp soft objects. However, the in-hand manipulation of these objects has proved to be challenging, with both soft fingertips and traditional designs, as the control of coordinated fine fingertip motions and uncertainties for soft materials are intricate. This paper presents a novel technique for in-hand manipulating soft objects with precision. The approach is based on enhancing the dexterity of robot hands via soft fingertips with tactile sensing and active shape changing; such that pressurized air cavities act as soft tactile sensors to provide closed loop control of fingertip position and avoid object’s damage, and pneumatic-tuned positive-pressure deformations act as a localized soft gripper to perform additional translations and rotations. We model the deformation of the soft fingertips to predict the in-hand manipulation of soft objects and experimentally demonstrate the resulting in-hand manipulationcapabilities of a gripper of limited dexterity with an algorithm based on the proposed dual abilities. Results show that the introduced approach can ease and enhance the prehensile in-hand translation and rotation of soft objects for precision tasks across the hand workspace, without damage.

Conference paper

Sadati SMH, Maiolino P, Iida F, Nanayakkara T, Hauser Het al., 2020, Editorial: current advances in soft robotics: best papers from RoboSoft 2018, Frontiers in Robotics and AI, Vol: 7, Pages: 1-2, ISSN: 2296-9144

Journal article

He L, Lu Q, Abad S-A, Rojas N, Nanayakkara DPTet al., 2020, Soft fingertips with tactile sensing and active deformation for robust grasping of delicate objects, IEEE Robotics and Automation Letters, Vol: 5, Pages: 2714-2721, ISSN: 2377-3766

Soft fingertips have shown significant adaptability for grasping a wide range of object shapes, thanks to elasticity. This ability can be enhanced to grasp soft, delicate objects by adding touch sensing. However, in these cases, the complete restraint and robustness of the grasps have proved to be challenging, as the exertion of additional forces on the fragile object can result in damage. This letter presents a novel soft fingertip design for delicate objects based on the concept of embedded air cavities, which allow the dual ability of tactile sensing and active shape-changing. The pressurized air cavities act as soft tactile sensors to control gripper position from internal pressure variation; and active fingertip deformation is achieved by applying positive pressure to these cavities, which then enable a delicate object to be kept securely in position, despite externally applied forces, by form closure. We demonstrate this improved grasping capability by comparing the displacement of grasped delicate objects exposed to high-speed motions. Results show that passive soft fingertips fail to restrain fragile objects at accelerations as low as 0.1 m/s 2 , in contrast, with the proposed fingertips delicate objects are completely secure even at accelerations of more than 5 m/s 2 .

Journal article

Xinyang T, He L, Cao J, Chen W, Nanayakkara DPTet al., 2020, A soft pressure sensor skin for hand and wrist orthoses, IEEE Robotics and Automation Letters, Vol: 5, Pages: 2192-2199, ISSN: 2377-3766

Side effects caused by excessive contact pressure such as discomfort and pressure sores are commonly complained by patients wearing orthoses. These problems leading to low patient compliance decrease the effectiveness of the device. To mitigate side effects, this study describes the design and fabrication of a soft sensor skin with strategically placed 12 sensor units for static contact pressure measurement beneath a hand and wrist orthosis. A Finite Element Model was built to simulate the pressure on the hand of a subject and sensor specifications were obtained from the result to guide the design. By testing the fabricated soft sensor skin on the subject, contact pressure between 0.012 MPa and 0.046 MPa was detected, revealing the maximum pressure at the thumb metacarpophalangeal joint which was the same location of the highest pressure of simulation. In this letter, a new fabrication method combining etching and multi-material additive manufacture was introduced to produce multiple sensor units as a whole. Furthermore, a novel fish-scale structure as the connection among sensors was introduced to stabilize sensor units and reinforce the soft skin. Experimental analysis reported that the sensor signal is repeatable, and the fish-scale structure facilitates baseline resuming of sensor signal during relaxation.

Journal article

Sadati H, Shiva A, Herzig N, Rucker C, Hauser H, Walker I, Bergeles C, Althoefer K, Nanayakkara DPTet al., 2020, Stiffness imaging with a continuum appendage: Real-time shape and tip force estimation from base load readings, IEEE Robotics and Automation Letters, Vol: 5, Pages: 2824-2831, ISSN: 2377-3766

In this letter, we propose benefiting from load readings at the base of a continuum appendage for real-time forward integration of Cosserat rod model with application in configuration and tip load estimation. The application of this method is successfully tested for stiffness imaging of a soft tissue, using a 3-DOF hydraulically actuated braided continuum appendage. Multiple probing runs with different actuation pressures are used for mapping the tissue surface shape and directional linear stiffness, as well as detecting non-homogeneous regions, e.g. a hard nodule embedded in a soft silicon tissue phantom. Readings from a 6-axis force sensor at the tip is used for comparison and verification. As a result, the tip force is estimated with 0.016–0.037 N (7–20%) mean error in the probing and 0.02–0.1 N (6–12%) in the indentation direction, 0.17 mm (14%) mean error is achieved in estimating the surface profile, and 3.4–15 [N/m] (10–16%) mean error is observed in evaluating tissue directional stiffness, depending on the appendage actuation. We observed that if the appendage bends against the slider motion (toward the probing direction), it provides better horizontal stiffness estimation and better estimation in the perpendicular direction is achieved when it bends toward the slider motion (against the probing direction). In comparison with a rigid probe, $\approx \!\!10$ times smaller stiffness and $\approx \!\!7$ times larger mean standard deviation values were observed, suggesting the importance of a probe stiffness in estimation the tissue stiffness.

Journal article

Scimeca L, Iida F, Maiolino P, Nanayakkara Tet al., 2020, Human-Robot Medical Interaction, 15th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI), Publisher: ASSOC COMPUTING MACHINERY, Pages: 660-661, ISSN: 2167-2121

Conference paper

Hughes J, Maiolino P, Nanayakkara T, Iida Fet al., 2020, Sensorized Phantom For Characterizing Large Area Deformation of Soft Bodies for Medical Applications, 3rd IEEE International Conference on Soft Robotics (RoboSoft), Publisher: IEEE, Pages: 278-284

Conference paper

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