Accenture Global Solutions Limited

Lavinia Andreea Danielescu

Mark Benjamin Greenspan

Aditi Maheshwari

Timothy M Shea

Kenneth Stewart

Eric Michael Gallo

Alexandria Emily Pabst

Jack Forman

Noah Gideon Pacik-Nelson

Ioannis Polykretis

Lazar Supic

Lingyi Bi

Kenneth Michael Stewart

Systems, methods, and devices are directed to providing charge mitigation via a MXene-based conductive pathway on a spacesuit. In one aspect, a system for planetary exploration to provide charge mitigation on an outer surface of the spacesuit comprises a multilayered fabric including a woven layer, wherein the woven layer includes a first side to face a space environment and an opposing side to face a body of a wearer of the spacesuit and a MXene coating layer applied on the opposing side, wherein the MXene coating layer extends through the thickness the woven layer to conductively couple a first location on an exterior surface of the spacesuit with a second location on the exterior surface of the spacesuit.

Providing charge mitigation on a spacesuit via a MXene-based conductive pathway

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for updating a trained gesture recognition model deployed on a neuromorphic processor that has been trained to process data that characterizes the new gesture and to determine a gesture classification for the gesture are described. A method includes receiving data that characterizes a new gesture and processing the data to generate a new embedding in a latent space. For each of multiple clusters of reference embeddings in the latent space, a respective distance in the latent space between the cluster of reference embedding and the new embedding is determined. A determination is made, based on applying one or more learning rules to the distances, one or more procedures to update the gesture recognition model. A determination is made, in accordance with the determined procedure(s), an update to values of one or more parameters of the gesture recognition model.

Self-learning neuromorphic gesture recognition models

Aspects of the present disclosure provide an environmental probe configured to be at least partially inserted into the ground at a location and to provide defensible space monitoring and maintenance for a home or other structure. The environmental probe may include one or more environmental sensors configured to perform various environmental measurements to generate environmental measurement data. The environmental probe (e.g., a processor of the environmental probe) may compare the environmental measurement data to one or more thresholds to determine an alert state associated with the location. The environmental probe may include one or more wireless interfaces configured to enable communication with a remote device, such as a smart hub device or other environmental probes. The environmental probe may transmit an indicator of the alert state to the remote device to enable performance of one or more operations based on the alert state.

Smart environmental probe for defensible space monitoring

This document describes self-cleaning devices. In one aspect, a self-cleaning device includes a fabric having a surface covered with a photocatalyst, one or more light sources embedded in the fabric, and a triggering mechanism that activates a cleaning cycle by activating the one or more light sources. The triggering mechanism can include a pressure sensor. The triggering mechanism can be configured to activate the cleaning cycle in response to detecting a decrease in pressure being applied to the pressure sensor.

Self-cleaning device

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for recognizing speech using a spiking neural network acoustic model implemented on a neuromorphic processor are described. In one aspect, a method includes receiving, a trained acoustic model implemented as a spiking neural network (SNN) on a neuromorphic processor of a client device, a set of feature coefficients that represent acoustic energy of input audio received from a microphone communicably coupled to the client device. The acoustic model is trained to predict speech sounds based on input feature coefficients. The acoustic model generates output data indicating predicted speech sounds corresponding to the set of feature coefficients that represent the input audio received from the microphone. The neuromorphic processor updates one or more parameters of the acoustic model using one or more learning rules and the predicted speech sounds of the output data.

Self-learning neuromorphic acoustic model for speech recognition

This document describes neuromorphic controllers. In one aspect, a method for controlling one or more joints of a robotic arm includes receiving, by neuromorphic controller comprising a spiking neural network (SNN), a target value of a joint control variable for a joint of the robotic arm. The SNN includes two position proprioceptor neurons, two-speed proprioceptor neurons, a presynaptic inhibitory neuron, an extensor motor neuron, and a flexor motor neuron. The neuromorphic controller updates an actual value of the joint control variable for the joint of the robotic arm based on the target value of the joint control variable. The updating includes generating, by one of the two position proprioceptor neurons, the first spikes to one of the extensors motor neurons or the flexor motor neuron based on a difference between the actual value of the joint control variable and the target value of the joint control variable.

Neuromorphic smooth control of robotic arms

Electrical input devices can be produced using a multi-material 3D-printing process. The electrical input devices can include a non-conductive material portion and a conductive material portion. The non-conductive and conductive material portions are integrally formed during a single 3D-printing process. Deformation of the electrical input devices cause an electrical variance of the conductive material portion that is responsive to the deformation. Some electrical input devices described provide digital responses, and some electrical input devices described provide analog responses. The described techniques can be used to manufacture complex finished devices in a single 3D-print run, and, in some examples, without the need for post-processing or assembly.

3D-printed deformable input devices

An upper-extremity prosthetic is adapted to engage with an athletic ball. The prosthetic includes one or more springs that provide energy return as a user is throwing the ball using the prosthetic. The springs can have a conductivity that changes in relation to an amount of strain or deformation of the spring. The change in conductivity can be used to provide haptic feedback to the user so the user can sense the amount of force being applied to throw the ball. In some embodiments, the springs are made by a multi-material 3D printing (additive manufacturing) process and include a first material that is electrically non-conductive and a second material that electrically conductive. In some embodiments, the prosthetic also includes one or more cantilevered springs that are also adapted to engage with the ball and to provide energy return while throwing the ball.

Upper extremity prosthetic with energy return system

This document described pressure-sensitive human machine interface (HMI) devices. In some aspects, a pressure-sensitive human-machine interface (HMI) device may include a surface element comprising an outer surface for receiving pressure inputs. The HMI device may also include multiple pressure-sensitive input regions that each include one or more positive electrodes and one or more return electrodes. The HMI device may also include a pressure-sensitive conductive sheet disposed adjacent to or between the one or more positive electrodes and one or more return electrodes of the multiple pressure-sensitive input regions.

Pressure-sensitive machine interface device

Springs can provide energy return and have a conductivity that changes in relation to an amount of strain or deformation of the spring. In some embodiments, the springs are made by multi-material 3D printing (additive manufacturing). Such springs made by multi-material 3D printing may include a first material that is electrically non-conductive and a second material that electrically conductive. The extent of deformation or strain of the spring may be determined or estimated by measuring the conductivity or resistivity of the electrically conductive material portion of the spring.

Springs with strain feedback

Implementations are directed to a pressure-sensing device including a pressure-sensitive sheet, one or more pressure-sensitive input regions disposed along the pressure-sensitive sheet including a first conductive thread including a first length in contact with the pressure-sensitive sheet, and a second conductive thread including a second length in contact with the pressure-sensitive sheet. At least a first portion of the first length of the first conductive thread passes through the pressure-sensitive sheet through a first hole in the pressure-sensitive sheet at a first location and a second portion of the second length of the second conductive thread passes through the pressure-sensitive sheet through a second hole in the pressure-sensitive sheet at a second location.

Flexible pressure sensors

This document describes morphing objects that are created using hydrogels and techniques for creating and controlling the morphing objects. In one aspect, a method for creating a morphing object includes creating one or more heating elements on a substrate by applying one or more conductive traces onto at least one of a first surface of the substrate or a second surface of the substrate opposite the first surface and forming a hydrogel pattern on the first surface of the substrate by applying a hydrogel ink to the first surface of the substrate based on a predefined pattern.

Creating morphing objects by inkjet printing thermoresponsive hydrogels

Implementations are directed to a smart filter apparatus including an air filter, a sensor supported by the air filter and sensitive to a pathogen, and a control unit in data communication with the sensor and operable to perform operations including receiving, from the sensor, an indication of the pathogen present in air incident on the sensor, generating, by the control unit, a pathogen alert response, and providing, by the control unit, the pathogen alert response.

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San Francisco, CA, United States of America

Lavinia Andreea Danielescu