Liver organoids (LOs) are of interest in tissue replacement, hepatotoxicity and pathophysiological studies. However, it is still unclear what triggers LO self-assembly and what the optimal environment is for their culture. Hypothesizing that LO formation occurs as a result of a fine balance between cell-substrate adhesion and cell-cell cohesion, we used 3 cell types (hepatocytes, liver sinusoidal endothelial cells and mesenchymal stem cells) to investigate LO self-assembly on different substrates keeping the culture parameters (e.g. culture media, cell types/number) and substrate stiffness constant. As cellular spheroids may suffer from oxygen depletion in the core, we also sought to identify the optimal culture conditions for LOs in order to guarantee an adequate supply of oxygen during proliferation and differentiation. The oxygen consumption characteristics of LOs were measured using an O2 sensor and used to model the O2 concentration gradient in the organoids. We show that no LO formation occurs on highly adhesive hepatic extra-cellular matrix-based substrates, suggesting that cellular aggregation requires an optimal trade-off between the adhesiveness of a substrate and the cohesive forces between cells and that this balance is modulated by substrate mechanics. Thus, in addition to substrate stiffness, physicochemical properties, which are also critical for cell adhesion, play a role in LO self-assembly.
About two decades ago, West and coworkers established a model which predicts that metabolic rate follows a three quarter power relationship with the mass of an organism, based on the premise that tissues are supplied nutrients through a fractal distribution network. Quarter power scaling is widely considered a universal law of biology and it is generally accepted that were in-vitro cultures to obey allometric metabolic scaling, they would have more predictive potential and could, for instance, provide a viable substitute for animals in research. This paper outlines a theoretical and computational framework for establishing quarter power scaling in three-dimensional spherical constructs in-vitro, starting where fractal distribution ends. Allometric scaling in non-vascular spherical tissue constructs was assessed using models of Michaelis Menten oxygen consumption and diffusion. The models demonstrate that physiological scaling is maintained when about 5 to 60% of the construct is exposed to oxygen concentrations less than the Michaelis Menten constant, with a significant concentration gradient in the sphere. The results have important implications for the design of downscaled in-vitro systems with physiological relevance.
Variable stiffness actuators (VSAs) are complex mechatronic devices that are developed to build passively compliant, robust, and dexterous robots. Numerous different hardware designs have been developed in the past two decades to address various demands on their functionality. This review paper gives a guide to the design process from the analysis of the desired tasks identifying the relevant attributes and their influence on the selection of different components such as motors, sensors, and springs. The influence on the performance of different principles to generate the passive compliance and the variation of the stiffness are investigated. Furthermore, the design contradictions during the engineering process are explained in order to find the best suiting solution for the given purpose. With this in mind, the topics of output power, potential energy capacity, stiffness range, efficiency, and accuracy are discussed. Finally, the dependencies of control, models, sensor setup, and sensor quality are addressed.
This study describes an actuated bioreactor which mimics the pulsatile contractile motion of the intestinal barrier using electro-responsive elastomers as smart materials that undergo deformation upon electrical stimulation. The device consists of an annular dielectric elastomer actuator working as a radial artificial muscle able to rhythmically contract and relax a central cell culture well. The bioreactor maintained up to 4 h of actuation at a frequency of 0.15 Hz and a strain of 8%–10%, to those of the cyclic contraction and relaxation of the small intestine. In vitro tests demonstrated that the device was biocompatible and cell-adhesive for Caco-2 cells, which formed a confluent monolayer following 21 days of culture in the central well. In addition, cellular adhesion and cohesion were maintained after 4 h of continuous cyclic strain. These preliminary results encourage further investigations on the use of dielectric elastomer actuation as a versatile technology that might overcome the limitations of commercially available pneumatic driving systems to obtain bioreactors that can cyclically deform cell cultures in a biomimetic fashion.
Soft robots are one of the most significant recent evolutions in robotics. They rely on compliant physical structures purposefully designed to embody desired characteristics. Since their introduction, they have shown remarkable applicability in overcoming their rigid counterparts in such areas as interaction with humans, adaptability, energy efficiency, and maximization of peak performance. Nonetheless, we believe
that research on novel soft robot applications is still slowed by the difficulty in obtaining or developing a working soft robot structure to explore novel applications.
In this article, we present the Natural Machine Motion Initiative (NMMI), a modular open platform that aims to provide the scientific community with tools for fast and easy prototyping of articulated soft robots. Such a platform is composed of three main open hardware modules: the Qbmoves variable-stiffness actuators (VSAs) to build the main robotic structure, soft end effectors (EEs) to interact with the world, and a pool of application-specific add-ons. We also discuss many novel uses of the platform to rapidly prototype (RP) and test new robotic structures with original soft capabilities, and we propose NMMI- based experiments.
Notes
Open access
e wish to thank Samuele Batazzi, Fabio Bonomo, Alberto
Brando, Andrea Di Basco, Tommaso Pardi, Riccardo Persichi-
ni, and Alessandro Raugi for their valuable support in the
development of the hardware prototype. This work was sup-
ported by SOFTPRO (grant 688857) and SOMA (grant
645599)—projects of the European Commission’s Horizon
2020 research program—and by Walk-Man grant 611832.
Support also came from the European Research Council
under an Advanced Grant for “SoftHands: A Theory of Soft
Synergies for a New Generation of Artificial Hands” (grant
Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.
We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation.
Notes
This work is supported in part by the European Research Council under the Advanced Grant “SoftHands: A Theory of Soft Synergies for a New Generation of Artificial Hands” (No. ERC-291166), by the EU H2020 projects “SoftPro: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn” (No. 688857) and “SOMA: Soft Manipulation” (No. 64559) and by the EU FP7 project (No. 601165) “WEARable HAPtics for Humans and Robots (WEARHAP)”.
A cooperative navigation procedure for a team of autonomous underwater vehicles (AUVs) is described and validated on experimental data. The procedure relies on acoustic communication networking among the AUVs and/or fixed acoustic nodes, and it is suitable as a low-cost solution for team navigation. Embedding the acoustic localization measurements in the communication scheme causes delays and sometimes loss of acoustic data, depending on acoustic propagation conditions. Despite this drawback, the results obtained show that on-board localization estimates have an error of the order of few meters, improving the overall navigation performance and leading the system towards long-term autonomy in terms of operating mission time, without the need of periodic resurfacings dedicated to reset the estimation error. The data were collected during the CommsNet ’13 experiment, led by the NATO Science and Technology Organization Center for Maritime Research and Experimentation (CMRE), and the Breaking The Surface ’14 workshop, organized by the University of Zagreb.
Attitude estimation is a crucial aspect for navigation and motion control of autonomous vehicles. This concept is particularly true in the case of unavailability of localization sensors when navigation and control rely on dead reckoning strategies; in this case, indeed, the orientation estimate is also used along with speed measurements to update the position estimate. Among the different approaches proposed in the literature, the de facto state of the art in this field is represented by nonlinear complementary filters: they fuse the measurements of angular rate obtained through gyroscopes, and a measurement of gravity and Earth’s magnetic field vectors respectively obtained through accelerometers and magnetometers. This paper is focused on an attitude estimation strategy for autonomous underwater vehicles (AUV). The proposed novelty includes the identification of some critical issues that arise when AUV attitude estimation algorithms are applied in practice.
They are mainly due to the use of low-accuracy low-cost microelectromechanical systems (MEMS) sensors and on different sources of magnetic disturbances. Some strategies to overcome the identified issues are proposed, including the integration of a single-axis fiber optic gyroscope (FOG) that ensures a considerable performance improvement with a moderate cost increase. The proposed strategies for detection of issues and sensor fusion have been experimentally tested and validated in a real application scenario estimating the attitude of an AUV performing a lawn mower path.
The expected performance improvement is confirmed; the obtained results are described and analyzed in this paper.
Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions involving one or more AUVs. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present a comparison between the Extended Kalman Filter (EKF) approach, classically used in the field of underwater robotics and an Unscented Kalman Filter (UKF). The comparison results to be significant as the two strategies of filtering are based on the same process and sensors models. The UKF-based approach, here adapted to the AUV case, demonstrates to be a good trade-off between estimation accuracy and computational load. UKF has not yet been extensively used in practical underwater applications, even if it turns out to be quite promising. The proposed results rely on the data acquired during a sea mission performed by one of the two Typhoon class vehicles involved in the NATO CommsNet13 experiment (held in September 2013). As ground truth for performance evaluation and comparison, performed offline, position measurements obtained through Ultra-Short BaseLine (USBL) fixes are used. The result analysis leads to identify both the strategies as effective for the purpose of being included in the control loop of an AUV. The UKF approach demonstrates higher performance encouraging its implementation as a more suitable navigation algorithm even if, up to now, it is still not used much in this field.
The development of precise and robust navigation strategies for Autonomous Underwater Vehicles (AUVs) is fundamental to reach the high level of performance required by complex underwater tasks, often including more than one AUV. One of the main factors affecting the accuracy of AUVs navigation systems is the algorithm used to estimate the vehicle motion, usually based on kinematic vehicle models and linear estimators. A precise and reliable navigation system is indeed fundamental to AUVs: the Global Positioning System (GPS) signal is not available underwater, thus making it very hard to know the position of the vehicle in real-time. In this paper, the authors present an innovative navigation strategy specifically designed for AUVs, based on the Unscented Kalman Filter (UKF). The new algorithm proves to be effective if applied to this class of vehicles and allows us to achieve a satisfying accuracy improvement compared to standard navigation algorithms. The proposed strategy has been experimentally validated using the navigation data acquired in suitable sea tests performed in Biograd Na Moru (Croatia) in the framework of the FP7 European ARROWS project tests performed during the Breaking the Surface 2014 (BtS 2014) workshop. The vehicles involved are the two Typhoon AUVs, developed and built by the Department of Industrial Engineering of the University of Florence within the THESAURUS Tuscany Region project for exploration and surveillance of underwater archaeological sites. The experiment, described in the paper, was performed to preliminary test the cooperative navigation between these AUVs. The new algorithm has been initially tested offline, and the validation of the proposed strategy provided accurate results in estimating the vehicle dynamic behaviour.
Myoelectric-artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human-likeness of prosthesis movements, a goal which is being pursued by research on social and human-robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed such as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an under-actuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro. The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e. flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step towards a more effective and intuitive control of myoelectric hand prostheses.
Understanding the mechanisms of human tactual perception represents a challenging task in haptics and humanoid robotics. A classic approach to tackle this issue is to accurately and exhaustively characterize the mechanical behavior of human fingertip. The output of this characterization can then be exploited to drive the design of numerical models, which can be used to investigate in depth the mechanisms of human sensing. In this work, we present a novel integrated measurement technique and experimental set up for in vivo characterization of the deformation of the human fingertip at contact, in terms of contact area, force, deformation, and pressure distribution. The device presented here compresses the participant's fingertip against a flat surface, while the aforementioned measurements are acquired and experimental parameters such as velocity, finger orientation, and displacement (indentation) controlled. Experimental outcomes are then compared and integrated with the output of a 3D finite element (FE) model of the human fingertip, built upon existing validated models. The agreement between numerical and experimental data represents a validation for our approach.
Tissue clarification has been recently proposed to allow deep tissue imaging without light scattering. The clarification parameters are somewhat arbitrary and dependent on tissue type, source and dimension: every laboratory has its own protocol, but a quantitative approach to determine the optimum clearing time is still lacking. Since the use of transgenic mouse lines that express fluorescent proteins to visualize specific cell populations is widespread, a quantitative approach to determine the optimum clearing time for genetically labeled neurons from thick murine brain slices using CLARITY2 is described. In particular, as the main objective of the delipidation treatment is to clarify tissues, while limiting loss of fluorescent signal, the “goodness” of clarification was evaluated by considering the bulk tissue clarification index (BTCi) and the fraction of the fluorescent marker retained in the slice as easily quantifiable macroscale parameters. Here we describe the approach, illustrating an example of how it can be used to determine the optimum clearing time for 1 mm-thick cerebellar slice from transgenic L7GFP mice, in which Purkinje neurons express the GFP (green fluorescent protein) tag. To validate the method, we evaluated confocal stacks of our samples using standard image processing indices (i.e., the mean pixel intensity of neurons and the contrast-to-noise ratio) as figures of merit for image quality. The results show that detergent-based delipidation for more than 5 days does not increase tissue clarity but the fraction of GFP in the tissue continues to diminish. The optimum clearing time for 1 mm-thick slices was thus identified as 5 days, which is the best compromise between the increase in light penetration depth due to removal of lipids and a decrease in fluorescent signal as a consequence of protein loss: further clearing does not improve tissue transparency, but only leads to more protein removal or degradation. The rigorous quantitative approach described can be generalized to any clarification method to identify the moment when the clearing process should be terminated to avoid useless protein loss.
Given the critical role of liver mechanics in regulating cell response and directing the development of tissue fibrosis, accurately characterising its mechanical behaviour is of relevance for both diagnostic purposes as well as for tissue engineering and for the development of in-vitro models. Determining and quantifying the mechanical behaviour of soft biological tissues is, however, highly challenging due to their intrinsic labile nature. Indeed, a unique set of values of liver mechanical properties is still lacking to date; testing conditions can significantly affect sample status and hence the measured behaviour and reported results are strongly dependent on the adopted testing method and configuration as well as sample type and status. This review aims at summarising the bulk mechanical properties of liver described in the literature, discussing the possible sources of variation and their implications on the reported results. We distinguish between the intrinsic mechanical behaviour of hepatic tissue, which depends on sample variables, and the measured mechanical properties which also depend on the testing and analysis methods. Finally, the review provides guidelines on tissue preparation and testing conditions for generating reproducible data which can be meaningfully compared across laboratories.
In this paper we consider the controllability problem for a system consisting of a pair of Dubins vehicles moving in a 3D space (i.e. pair of 3D–Dubins vehicles) while maintaining constant distance. Necessary and sufficient conditions for the existence of a limited control effort to steer the system between any two configurations are provided. The proposed controllability analysis and the developed motion planning algorithm are a step toward the solution of planning problems for example in case the robots are physically constrained to a payload to be deployed. Moreover, results obtained in this paper are relevant in order to solve formation control problems for multiple robots as aerial or underwater vehicles, which move in 3D spaces. Simulation results highlight the sufficiency of the obtained conditions showing that even from critical configurations an admissible control can be determined.
A software and control architecture for a humanoid robot is a complex and large project, which involves a team of developers/researchers to be coordinated and requires many hard design choices. If such project has to be done in a very limited time, i.e., less than 1 year, more constraints are added and concepts, such as modular design, code reusability, and API definition, need to be used as much as possible. In this work, we describe the software architecture developed for Walk-Man, a robot participant at the Darpa Robotics Challenge. The challenge required the robot to execute many different tasks, such as walking, driving a car, and manipulating objects. These tasks need to be solved by robotics specialists in their corresponding research field, such as humanoid walking, motion planning, or object manipulation. The proposed architecture was developed in 10 months, provided boilerplate code for most of the functionalities required to control a humanoid robot and allowed robotics researchers to produce their control modules for DRC tasks in a short time. Additional capabilities of the architecture include firmware and hardware management, mixing of different middlewares, unreliable network management, and operator control station GUI. All the source code related to the architecture and some control modules have been released as open source projects.
