Neural dynamics of robust legged robots.

Legged robot control has improved in recent years with the rise of deep reinforcement learning, however, much of the underlying neural mechanisms remain difficult to interpret. Our aim is to leverage bio-inspired methods from computational neuroscience to better understand the neural activity of robust robot locomotion controllers. Similar to past work, we observe that terrain-based curriculum learning improves agent stability. We study the biomechanical responses and neural activity within our neural network controller by simultaneously pairing physical disturbances with targeted neural ablations. We identify an agile hip reflex that enables the robot to regain its balance and recover from lateral perturbations. Model gradients are employed to quantify the relative degree that various sensory feedback channels drive this reflexive behavior. We also find recurrent dynamics are implicated in robust behavior, and utilize sampling-based ablation methods to identify these key neurons. Our framework combines model-based and sampling-based methods for drawing causal relationships between neural network activity and robust embodied robot behavior.

Distributed IMU Sensors for In-Field Dynamic Measurements on an Alpine Ski.

Modern ski design is an inherently time-consuming process that involves an iterative feedback loop comprised of design, manufacturing and in-field qualitative evaluations. Additionally consumers can only rely on qualitative evaluation for selecting the ideal ski, and due to the variation in skier styles and ability levels, consumers can find it to be an inconsistent and expensive experience. We propose supplementing the design and evaluation process with data from in-field prototype testing, using a modular sensor array that can be ported to nearly any ski. This paper discusses a new distributed Inertial Measurement Unit (IMU) suite, including details regarding the design and operation, sensor validation experiments, and outdoor in-field testing results. Data are collected from a set of spatially distributed IMUs located on the upper surface of the ski. We demonstrate that this system and associated post-processing algorithms provide accurate data at a high rate (>700 Hz), enabling the measurement of both structural and rigid ski characteristics, and are robust to repetitive testing in outdoor winter conditions.

A multifunctional soft robotic shape display with high-speed actuation, sensing, and control.

Shape displays which actively manipulate surface geometry are an expanding robotics domain with applications to haptics, manufacturing, aerodynamics, and more. However, existing displays often lack high-fidelity shape morphing, high-speed deformation, and embedded state sensing, limiting their potential uses. Here, we demonstrate a multifunctional soft shape display driven by a 10 × 10 array of scalable cellular units which combine high-speed electrohydraulic soft actuation, magnetic-based sensing, and control circuitry. We report high-performance reversible shape morphing up to 50 Hz, sensing of surface deformations with 0.1 mm sensitivity and external forces with 50 mN sensitivity in each cell, which we demonstrate across a multitude of applications including user interaction, image display, sensing of object mass, and dynamic manipulation of solids and liquids. This work showcases the rich multifunctionality and high-performance capabilities that arise from tightly-integrating large numbers of electrohydraulic actuators, soft sensors, and controllers at a previously undemonstrated scale in soft robotics.

Lidar-Based Navigation of Subterranean Environments Using Bio-Inspired Wide-Field Integration of Nearness.

Navigating unknown environments is an ongoing challenge in robotics. Processing large amounts of sensor data to maintain localization, maps of the environment, and sensible paths can result in high compute loads and lower maximum vehicle speeds. This paper presents a bio-inspired algorithm for efficiently processing depth measurements to achieve fast navigation of unknown subterranean environments. Animals developed efficient sensorimotor convergence approaches, allowing for rapid processing of large numbers of spatially distributed measurements into signals relevant for different behavioral responses necessary to their survival. Using a spatial inner-product to model this sensorimotor convergence principle, environmentally relative states critical to navigation are extracted from spatially distributed depth measurements using derived weighting functions. These states are then applied as feedback to control a simulated quadrotor platform, enabling autonomous navigation in subterranean environments. The resulting outer-loop velocity controller is demonstrated in both a generalized subterranean environment, represented by an infinite cylinder, and nongeneralized environments like tunnels and caves.

Miniaturized Circuitry for Capacitive Self-Sensing and Closed-Loop Control of Soft Electrostatic Transducers.

Soft robotics is a field of robotic system design characterized by materials and structures that exhibit large-scale deformation, high compliance, and rich multifunctionality. The incorporation of soft and deformable structures endows soft robotic systems with the compliance and resiliency that makes them well adapted for unstructured and dynamic environments. Although actuation mechanisms for soft robots vary widely, soft electrostatic transducers such as dielectric elastomer actuators (DEAs) and hydraulically amplified self-healing electrostatic (HASEL) actuators have demonstrated promise due to their muscle-like performance and capacitive self-sensing capabilities. Despite previous efforts to implement self-sensing in electrostatic transducers by overlaying sinusoidal low-voltage signals, these designs still require sensing high-voltage signals, requiring bulky components that prevent integration with miniature untethered soft robots. We present a circuit design that eliminates the need for any high-voltage sensing components, thereby facilitating the design of simple low cost circuits using off-the-shelf components. Using this circuit, we perform simultaneous sensing and actuation for a range of electrostatic transducers including circular DEAs and HASEL actuators and demonstrate accurate estimated displacements with errors <4%. We further develop this circuit into a compact and portable system that couples high voltage actuation, sensing, and computation as a prototype toward untethered multifunctional soft robotic systems. Finally, we demonstrate the capabilities of our self-sensing design through feedback control of a robotic arm powered by Peano-HASEL actuators.

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories.

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Robust analysis of an underwater navigational strategy in electrically heterogeneous corridors.

Obstacles and other global stimuli provide relevant navigational cues to a weakly electric fish. In this work, robust analysis of a control strategy based on electrolocation for performing obstacle avoidance in electrically heterogeneous corridors is presented and validated. Static output feedback control is shown to achieve the desired goal of reflexive obstacle avoidance in such environments in simulation and experimentation. The proposed approach is computationally inexpensive and readily implementable on a small scale underwater vehicle, making underwater autonomous navigation feasible in real-time.

Diagnostic and medical strategy for renovascular hypertension: report from a monocentric pediatric cohort.

UNLABELLED: Renovascular hypertension accounts for 5-10 % of hypertension cases in children; there is currently no consensus on treatment. Here, we report on our clinical experience with this disease and outline the different pathways in which to investigate it. We report retrospectively on ten children diagnosed with renovascular hypertension at the University Hospital of Nantes from 2001 to 2012. The main findings were obtained by fortuitous screening of children aged 2 months to 14 years old with neurofibromatosis (n = 2) and fibromuscular dysplasia (n = 8). The hypertension was always severe yet asymptomatic. Lesions were complicated in nine out of ten cases and included bilateral, multiple, mid-aortic syndrome and aneurysm. Doppler ultrasound associated with computed tomography allowed for a precise diagnosis in seven out of ten cases. Where ambiguities persisted, they were highlighted by arteriography, the gold standard investigation. Medical treatment was insufficient, leading to invasive procedures in nine out of ten children: 2 nephrectomies, 2 autotransplantations, and 21 repetitive percutaneous transluminal angioplasties. After invasive procedures, blood pressure control improved in four cases and was resolved in three. CONCLUSION: Arteriography remains to be the gold standard technique for renovascular hypertension in children and can be combined with angioplasty when medical treatment is rendered obsolete. The role of computed tomography is controversial. Despite the heterogeneity of the children studied, we present a general medical and therapeutic management pathway for the treatment of this disease.

Bio-inspired modeling and implementation of the ocelli visual system of flying insects.

Two visual sensing modalities in insects, the ocelli and compound eyes, provide signals used for flight stabilization and navigation. In this article, a generalized model of the ocellar visual system is developed for a 3-D visual simulation environment based on behavioral, anatomical, and electrophysiological data from several species. A linear measurement model is estimated from Monte Carlo simulation in a cluttered urban environment relating state changes of the vehicle to the outputs of the ocellar model. A fully analog-printed circuit board sensor based on this model is designed and fabricated. Open-loop characterization of the sensor to visual stimuli induced by self motion is performed. Closed-loop stabilizing feedback of the sensor in combination with optic flow sensors is implemented onboard a quadrotor micro-air vehicle and its impulse response is characterized.

Wing motion transformation to evaluate aerodynamic coupling in flapping wing flight.

Whether the remarkable flight performance of insects is because the animals leverage inherent physics at this scale or because they employ specialized neural feedback mechanisms is an active research question. In this study, an empirically derived aerodynamics model is used with a transformation involving a delay and a rotation to identify a class of kinematics that provide favorable roll-yaw coupling. The transformation is also used to transform both synthetic and experimentally measured wing motions onto the manifold representing proverse yaw and to quantify the degree to which freely flying insects make use of passive aerodynamic mechanisms to provide proverse roll-yaw turn coordination. The transformation indicates that recorded insect kinematics do act to provide proverse yaw for a variety of maneuvers. This finding suggests that passive aerodynamic mechanisms can act to reduce the neural feedback demands of an insect׳s flight control strategy.

A µ analysis-based, controller-synthesis framework for robust bioinspired visual navigation in less-structured environments.

Safe, autonomous navigation by aerial microsystems in less-structured environments is a difficult challenge to overcome with current technology. This paper presents a novel visual-navigation approach that combines bioinspired wide-field processing of optic flow information with control-theoretic tools for synthesis of closed loop systems, resulting in robustness and performance guarantees. Structured singular value analysis is used to synthesize a dynamic controller that provides good tracking performance in uncertain environments without resorting to explicit pose estimation or extraction of a detailed environmental depth map. Experimental results with a quadrotor demonstrate the vehicle's robust obstacle-avoidance behaviour in a straight line corridor, an S-shaped corridor and a corridor with obstacles distributed in the vehicle's path. The computational efficiency and simplicity of the current approach offers a promising alternative to satisfying the payload, power and bandwidth constraints imposed by aerial microsystems.

Electrolocation-based underwater obstacle avoidance using wide-field integration methods.

Weakly electric fish are capable of efficiently performing obstacle avoidance in dark and navigationally challenging aquatic environments using electrosensory information. This sensory modality enables extraction of relevant proximity information about surrounding obstacles by interpretation of perturbations induced to the fish's self-generated electric field. In this paper, reflexive obstacle avoidance is demonstrated by extracting relative proximity information using spatial decompositions of the perturbation signal, also called an electric image. Electrostatics equations were formulated for mathematically expressing electric images due to a straight tunnel to the electric field generated with a planar electro-sensor model. These equations were further used to design a wide-field integration based static output feedback controller. The controller was implemented in quasi-static simulations for environments with complicated geometries modelled using finite element methods to demonstrate sense and avoid behaviours. The simulation results were confirmed by performing experiments using a computer operated gantry system in environments lined with either conductive or non-conductive objects acting as global stimuli to the field of the electro-sensor. The proposed approach is computationally inexpensive and readily implementable, making underwater autonomous navigation in real-time feasible.

Comparative sensitivity to the fungicide tebuconazole of biofilm and plankton microbial communities in freshwater ecosystems.

Stream and lake ecosystems in agricultural watersheds are exposed to fungicide inputs that can threaten the structure and functioning of aquatic microbial communities. This research analyzes the impact of the triazole fungicide tebuconazole (TBZ) on natural biofilm and plankton microbial communities from sites presenting different degrees of agricultural contamination. Biofilm and plankton communities from less-polluted (LP) and polluted (P) sites were exposed to nominal concentrations of 0 (control), 2 and 20 µg TBZ L(-1) in 3-week microcosm experiments. Descriptors of microbial community structure (bacterial density and chlorophyll-a concentration) and function (bacterial respiration and production and photosynthesis) were analyzed to chart the effects of TBZ and the kinetics of TBZ attenuation in water during the experiments. The results showed TBZ-induced effects on biofilm function (inhibition of substrate-induced respiration and photosynthetic activity), especially in LP-site communities, whereas plankton communities experienced a transitory stimulation of bacterial densities in communities from both LP and P sites. TBZ attenuation was stronger in biofilm (60-75%) than plankton (15-18%) experiments, probably due to greater adsorption on biofilms. The differences between biofilm and plankton responses to TBZ were likely explained by differences in community structure (presence of extracellular polymeric substances (EPS) matrix) and microbial composition. Biofilm communities also exhibited different sensitivity levels according to their in-field pre-exposure to fungicide, with P-site communities demonstrating adaptation capacities to TBZ. This study indicates that TBZ toxicity to non-targeted aquatic microbial communities essentially composed by microalgae and bacteria was moderate, and that its effects varied between stream and lake microbial communities.

Next-generation sequencing to inventory taxonomic diversity in eukaryotic communities: a test for freshwater diatoms.

The recent emergence of barcoding approaches coupled to those of next-generation sequencing (NGS) has raised new perspectives for studying environmental communities. In this framework, we tested the possibility to derive accurate inventories of diatom communities from pyrosequencing outputs with an available DNA reference library. We used three molecular markers targeting the nuclear, chloroplast and mitochondrial genomes (SSU rDNA, rbcL and cox1) and three samples of a mock community composed of 30 known diatom strains belonging to 21 species. In the goal to detect methodological biases, one sample was constituted directly from pooled cultures, whereas the others consisted of pooled PCR products. The NGS reads obtained by pyrosequencing (Roche 454) were compared first to a DNA reference library including the sequences of all the species used to constitute the mock community, and second to a complete DNA reference library with a larger taxonomic coverage. A stringent taxonomic assignation gave inventories that were compared to the real one. We detected biases due to DNA extraction and PCR amplification that resulted in false-negative detection. Conversely, pyrosequencing errors appeared to generate false positives, especially in case of closely allied species. The taxonomic coverage of DNA reference libraries appears to be the most crucial factor, together with marker polymorphism which is essential to identify taxa at the species level. RbcL offers a high resolving power together with a large DNA reference library. Although needing further optimization, pyrosequencing is suitable for identifying diatom assemblages and may find applications in the field of freshwater biomonitoring.

Dramatic changes in a phytoplankton community in response to local and global pressures: a 24-year survey of the river Loire (France).

The impact of climate change and of other anthropogenic pressures on the structure and composition of phytoplankton communities of large European rivers remains poorly documented. Here we report the findings of a study of the changes in the phytoplankton community of the middle segment of the river Loire over the past 24 years. An attempt is made to distinguish between the impact of changes acting at the local scale and that of those acting more globally. A dramatic reduction in phytoplankton abundance was observed, particularly in the mid -1990s; this was concomitant with an increase in the relative proportion of cyanobacteria. At the same time, the phytoplankton community displayed increasing richness and diversity, and little change in its size structure. All these changes seem to be related to local changes, in particular to the reduction in phosphorus concentrations, as well as to changes in climate, throughout modifications in the river discharge and water temperature. Interestingly, herbicide contamination also appeared to be of particular importance in explaining the unexpected increase in the proportion of cyanobacteria in the phytoplankton community after the 1990s. These findings suggest that combinations of numerous anthropogenic pressures acting at different spatial and temporal scales have led to a mix of predictable and unpredictable changes occurring in the phytoplankton community of the river Loire, with probable consequences for the trophic networks in this river.

Kinematic strategies for mitigating gust perturbations in insects.

Insects are attractive models for the development of micro-aerial vehicles (MAVs) due to their relatively simple sensing, actuation and control architectures as compared to vertebrates, and because of their robust flight ability in dynamic and heterogeneous environments, characterized by turbulence and gusts of wind. How do insects respond to gust perturbations? We investigated this question by perturbing freely-flying honey bees and stalk-eye flies with low-pressure bursts of compressed air to simulate a wind gust. Body and wing kinematics were analyzed from flight sequences, recorded using three high-speed digital video cameras. Bees quickly responded to body rotations caused by gusts through bilateral asymmetry in stroke amplitude, whereas stalk-eye flies used a combination of asymmetric stroke amplitude and wing rotation angle. Both insects coordinated asymmetric and symmetric kinematics in response to gusts, which provides model strategies for simple yet robust flight characteristics for MAVs.

Measles virus glycoprotein-pseudotyped lentiviral vectors are highly superior to vesicular stomatitis virus G pseudotypes for genetic modification of monocyte-derived dendritic cells.

Dendritic cells (DCs) are potent antigen-presenting cells capable of promoting or regulating innate and adaptive immune responses against non-self antigens. To better understand the DC biology or to use them for immune intervention, a tremendous effort has been made to improve gene transfer in these cells. Lentiviral vectors (LVs) have conferred a huge advantage in that they can transduce nondividing cells such as human monocyte-derived DCs (MDDCs) but required high amounts of viral particles and/or accessory proteins such as Vpx or Vpr to achieve sufficient transduction rates. As a consequence, these LVs have been shown to cause dramatic functional modifications, such as the activation or maturation of transduced MDDCs. Taking advantage of new pseudotyped LVs, i.e., with envelope glycoproteins from the measles virus (MV), we demonstrate that MDDCs are transduced very efficiently with these new LVs compared to the classically used vesicular stomatitis virus G-pseudotyped LVs and thus allowed to achieve high transduction rates at relatively low multiplicities of infection. Moreover, in this experimental setting, no activation or maturation markers were upregulated, while MV-LV-transduced cells remained able to mature after an appropriate Toll-like receptor stimulation. We then demonstrate that our MV-pseudotyped LVs use DC-SIGN, CD46, and CD150/SLAM as receptors to transduce MDDCs. Altogether, our results show that MV-pseudotyped LVs provide the most accurate and simple viral method for efficiently transferring genes into MDDCs without affecting their activation and/or maturation status.

Optic flow estimation on trajectories generated by bio-inspired closed-loop flight.

We generated panoramic imagery by simulating a fly-like robot carrying an imaging sensor, moving in free flight through a virtual arena bounded by walls, and containing obstructions. Flight was conducted under closed-loop control by a bio-inspired algorithm for visual guidance with feedback signals corresponding to the true optic flow that would be induced on an imager (computed by known kinematics and position of the robot relative to the environment). The robot had dynamics representative of a housefly-sized organism, although simplified to two-degree-of-freedom flight to generate uniaxial (azimuthal) optic flow on the retina in the plane of travel. Surfaces in the environment contained images of natural and man-made scenes that were captured by the moving sensor. Two bio-inspired motion detection algorithms and two computational optic flow estimation algorithms were applied to sequences of image data, and their performance as optic flow estimators was evaluated by estimating the mutual information between outputs and true optic flow in an equatorial section of the visual field. Mutual information for individual estimators at particular locations within the visual field was surprisingly low (less than 1 bit in all cases) and considerably poorer for the bio-inspired algorithms that the man-made computational algorithms. However, mutual information between weighted sums of these signals and comparable sums of the true optic flow showed significant increases for the bio-inspired algorithms, whereas such improvement did not occur for the computational algorithms. Such summation is representative of the spatial integration performed by wide-field motion-sensitive neurons in the third optic ganglia of flies.

Pivotal advance: The promotion of soluble DC-SIGN release by inflammatory signals and its enhancement of cytomegalovirus-mediated cis-infection of myeloid dendritic cells.

DC-SIGN is a member of the C-type lectin family. Mainly expressed by myeloid DCs, it is involved in the capture and internalization of pathogens, including human CMV. Several transcripts have been identified, some of which code for putative soluble proteins. However, little is known about the regulation and the functional properties of such putative sDC-SIGN variants. To better understand how sDC-SIGN could be involved in CMV infection, we set out to characterize biochemical and functional properties of rDC-SIGN as well as naturally occurring sDC-SIGN. We first developed a specific, quantitative ELISA and then used it to detect the presence sDC-SIGN in in vitro-generated DC culture supernatants as cell-free secreted tetramers. Next, in correlation with their inflammatory status, we demonstrated the presence of sDC-SIGN in several human body fluids, including serum, joint fluids, and BALs. CMV infection of human tissues was also shown to promote sDC-SIGN release. Based on the analysis of the cytokine/chemokine content of sDC-SIGN culture supernatants, we identified IFN-γ and CXCL8/IL-8 as inducers of sDC-SIGN production by MoDC. Finally, we demonstrated that sDC-SIGN was able to interact with CMV gB under native conditions, leading to a significant increase in MoDC CMV infection. Overall, our results confirm that sDC-SIGN, like its well-known, counterpart mDC-SIGN, may play a pivotal role in CMV-mediated pathogenesis.

From falling to flying: the path to powered flight of a robotic samara nano air vehicle.

This paper details the development of a nano-scale (>15 cm) robotic samara, or winged seed. The design of prototypes inspired by naturally occurring geometries is presented along with a detailed experimental process which elucidates similarities between mechanical and robotic samara flight dynamics. The helical trajectories of a samara in flight were observed to differ in-flight path and descent velocity. The body roll and pitch angular rates for the differing trajectories were observed to be coupled to variations in wing pitch, and thus provide a means of control. Inspired by the flight modalities of the bio-inspired samaras, a robotic device has been created that mimics the autorotative capability of the samara, whilst providing the ability to hover, climb and translate. A high-speed camera-based motion capture system is used to observe the flight dynamics of the mechanical and robotic samara. Similarities in the flight dynamics are compared and discussed as it relates to the design of the robotic samara.