A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network's throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two classification tasks.Comment: 18 Pages main text, 9 pages of supplementary text, 19 figures. Patente

A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation

Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility features, they are characterized by computationally relevant physical properties, such as state-dependence, non-linear conductance changes, and intrinsic variability in both their switching threshold and conductance values, that make them ideal devices for emulating the bio-physics of real synapses. In this paper we present a spiking neural network architecture that supports the use of memristive devices as synaptic elements, and propose mixed-signal analog-digital interfacing circuits which mitigate the effect of variability in their conductance values and exploit their variability in the switching threshold, for implementing stochastic learning. The effect of device variability is mitigated by using pairs of memristive devices configured in a complementary push-pull mechanism and interfaced to a current-mode normalizer circuit. The stochastic learning mechanism is obtained by mapping the desired change in synaptic weight into a corresponding switching probability that is derived from the intrinsic stochastic behavior of memristive devices. We demonstrate the features of the CMOS circuits and apply the architecture proposed to a standard neural network hand-written digit classification benchmark based on the MNIST data-set. We evaluate the performance of the approach proposed on this benchmark using behavioral-level spiking neural network simulation, showing both the effect of the reduction in conductance variability produced by the current-mode normalizer circuit, and the increase in performance as a function of the number of memristive devices used in each synapse.Comment: 13 pages, 12 figures, accepted for Faraday Discussion

An ultra-low-power sigma-delta neuron circuit

Neural processing systems typically represent data using leaky integrate and fire (LIF) neuron models that generate spikes or pulse trains at a rate proportional to their input amplitudes. This mechanism requires high firing rates when encoding time-varying signals, leading to increased power consumption. Neuromorphic systems that use adaptive LIF neuron models overcome this problem by encoding signals in the relative timing of their output spikes rather than their rate. In this paper, we analyze recent adaptive LIF neuron circuit implementations and highlight the analogies and differences between them and a first-order sigma-delta feedback loop. We propose a new sigma-delta neuron circuit that addresses some of the limitations in existing implementations and present simulation results that quantify the improvements. We show that the new circuit, implemented in a 1.8 V, 180 nm CMOS process, offers up to 42 dB signal-to-distortion ratio and consumes orders of magnitude lower energy. Finally, we also demonstrate how the sigma-delta interpretation enables mapping of real-valued recurrent neural network to the spiking framework to emphasize the envisioned application of the proposed circuit.Comment: Submitted to TCAS-II Briefs. Reference code online-https://github.com/manuvn/sigma-delta-neural-networks.gi

Paget-Schroetter Syndrome: Review of Pathogenesis and Treatment of Effort Thrombosis

Effort thrombosis, or Paget-Schroetter Syndrome, refers to axillary-subclavian vein thrombosis associated with strenuous and repetitive activity of the upper extremities. Anatomical abnormalities at the thoracic outlet and repetitive trauma to the endothelium of the subclavian vein are key factors in its initiation and progression. The role of hereditary and acquired thrombophilias is unclear. The pathogenesis of effort thrombosis is thus distinct from other venous thromboembolic disorders. Doppler ultrasonography is the preferred initial test, while contrast venography remains the gold standard for diagnosis. Computed tomographic venography and magnetic resonance venography are comparable to conventional venography and are being increasingly used. Conservative management with anticoagulation alone is inadequate and leads to significant residual disability. An aggressive multimodal treatment strategy consisting of catheter-directed thrombolysis, with or without early thoracic outlet decompression, is essential for optimizing outcomes. Despite excellent insights into its pathogenesis and advances in treatment, a significant number of patients with effort thrombosis continue to be treated suboptimally. Hence, there is an urgent need for increasing physician awareness about risk factors, etiology and the management of this unique and relatively infrequent disorder

Design Engineering a Walking Robotic Manipulator for In-Space Assembly Missions

In-Space Services aim to introduce sustainable futuristic technology to support the current and growing orbital ecosystem. As the scale of space missions grows, there is a need for more extensive infrastructures in orbit. In-Space Assembly missions would hold one of the key responsibilities in meeting the increasing demand. In the forthcoming decades, newer infrastructures in the Earth’s orbits, which are much more advanced than the International Space Station are needed for in-situ manufacturing, servicing, and astronomical and observational stations. The prospect of in-orbit commissioning a Large Aperture Space Telescope (LAST) has fuelled scientific and commercial interests in deep-space astronomy and Earth Observation. However, the in-situ assembly of such large-scale, high-value assets in extreme environments, like space, is highly challenging and requires advanced robotic solutions. This paper introduces an innovative dexterous walking robotic system for in-orbit assembly missions and considers the Large Aperture Space Telescope system with an aperture of 25m as the use case. The top-level assembly requirements are identified with a deep insight into the critical functionalities and challenges to overcome while assembling the modular LAST. The design and sizing of an End-over-end Walking Robot (E-Walker) are discussed based on the design of the LAST and the specifications of the spacecraft platform. The E-Walker’s detailed design engineering includes the structural finite element analysis results for space and earth-analogue design and the corresponding actuator selection methods. Results of the modal analysis demonstrate the deflections in the E-Walker links and end-effector in the open-loop due to the extremities present in the space environment. The design and structural analysis of E-Walker’s scaled-down prototype is also presented to showcase its feasibility in supporting both in-orbit and terrestrial activities requiring robotic capabilities over an enhanced workspace. Further, the mission concept of operations is presented based on two E-Walkers that carry out the assembly of the mirror modules. The mission discussed was shortlisted after conducting an extensive trade-off study in the literature. Simulated results prove the dual E-Walker robotic system’s efficacy for accomplishing complex in-situ assembly operations through task-sharing

Modeling a Controlled-Floating Space Robot for In-Space Services: A Beginner’s Tutorial

Ground-based applications of robotics and autonomous systems (RASs) are fast advancing, and there is a growing appetite for developing cost-effective RAS solutions for in situ servicing, debris removal, manufacturing, and assembly missions. An orbital space robot, that is, a spacecraft mounted with one or more robotic manipulators, is an inevitable system for a range of future in-orbit services. However, various practical challenges make controlling a space robot extremely difficult compared with its terrestrial counterpart. The state of the art of modeling the kinematics and dynamics of a space robot, operating in the free-flying and free-floating modes, has been well studied by researchers. However, these two modes of operation have various shortcomings, which can be overcome by operating the space robot in the controlled-floating mode. This tutorial article aims to address the knowledge gap in modeling complex space robots operating in the controlled-floating mode and under perturbed conditions. The novel research contribution of this article is the refined dynamic model of a chaser space robot, derived with respect to the moving target while accounting for the internal perturbations due to constantly changing the center of mass, the inertial matrix, Coriolis, and centrifugal terms of the coupled system; it also accounts for the external environmental disturbances. The nonlinear model presented accurately represents the multibody coupled dynamics of a space robot, which is pivotal for precise pose control. Simulation results presented demonstrate the accuracy of the model for closed-loop control. In addition to the theoretical contributions in mathematical modeling, this article also offers a commercially viable solution for a wide range of in-orbit missions

Linear controllers for free-flying and controlled-floating space robots: a new perspective

Autonomous space robots are crucial for performing future in-orbit operations, including servicing of a spacecraft, assembly of large structures, maintenance of other space assets and active debris removal. Such orbital missions require servicer spacecraft equipped with one or more dexterous manipulators. However, unlike its terrestrial counterpart, the base of the robotic manipulator is not fixed in inertial space; instead, it is mounted on the base�spacecraft, which itself possess both translational and rotational motions. Additionally, the system will be subjected to extreme environmental perturbations, parametric uncertainties and system constraints due to the dynamic coupling between the manipulator and the base-spacecraft. This paper presents the dynamic model of the space robot and a three�stage control algorithm for this highly dynamic non-linear system. In this approach, feed�forward compensation and feed-forward linearization techniques are used to decouple and linearize the highly non-linear system respectively. This approach allows the use of the linear Proportional-Integral-Derivative (PID) controller and Linear Quadratic Regulator (LQR) in the final stages. Moreover, this paper covers a simulation-based trade-off analysis to determine both proposed linear controllers’ efficacy. This assessment considers precise trajectory tracking requirements whilst minimizing power consumption and improving robustness during the close-range operation with the target spacecraft

On Robotic In-Orbit Assembly of Large Aperture Space Telescopes

Space has found itself amidst numerous missions benefitting the life on Earth and for mankind to explore further. The space community has been in the move of launching various on-orbit missions, tackling the extremities of the space environment, with the use of robots, for performing tasks like assembly, maintenance, repairs, etc. The urge to explore further in the universe for scientific benefits has found the rise of modular Large-Space Telescopes (LASTs). With respect to the challenges of the in-space assembly of LAST, a five Degrees-of Freedom (DoF) End-Over-End Walking Robot (E-Walker) is presented in this paper. The Dynamical Model and Gait Pattern of the E-Walker is discussed with reference to the different phases of its motion. For the initial verification of the E-Walker model, a PID controller was used to make the E-Walker follow the desired trajectory. A mission concept discussing a potential strategy of assembling a 25m LAST with 342 Primary Mirror Units (PMUs) is briefly discussed. Simulation results show the precise tracking of the E-Walker along a desired trajectory is achieved without exceeding the joint torques

Advances in Robotic In-Orbit Assembly of Large Aperture Space Telescopes

Modular Large Aperture Space Telescopes (LAST) hold the key to future astronomical missions in search of the origin of the cosmos. Robotics and Autonomous Systems technology would be required to meet the challenges associated with the assembly of such high value infrastructure in orbit. In this paper an End-Over-End walking robot is selected to assemble a 25m LAST. The dynamical model, control architecture and gait pattern of the E-Walker are discussed. The key mission requirements are stated along with the strategies for scheduling the assembly process. A mission concept of operations (ConOps) is proposed for assembling the 25m LAST. Simulation results show the precise trajectory tracking of the EWalker for the chosen mission scenario