Elion IP, S.L

The present disclosure relates to a computer implemented method for computing a protection level PL of a state estimate p̂ from a provided input state estimate p₀; the method comprising:- obtaining an initial state estimate p_c which lies in a given subspace S;- obtaining a matrix F of partial derivatives of a local parametrisation f of the given subspace S around the initial state estimate p_c, which local parametrisation f is a function of a set of parameters α;- computing the state estimate p̂ as follows: p^=pc+F⋅Δα wherein:∘ Δα=H^TWH^−1H^TWrc,∘ H^=H⋅F,o H is a provided observation matrix,o W is a weighting matrix,o r_c is an initial vector of residuals computed as: rc=r0+Hp0−pcr₀ being a provided input vector of residuals;wherein the protection level PL of the state estimate p̂ is computed as: PL=k⋅r^W⋅Gk being a scalar factor, r̂ being a vector of residuals, r^W=r^TWr^, and G being a geometric factor computed using the matrix F.

The disclosure relates to a computer implemented method (100) for computing a protection level PL of a state estimate xc, the method comprising using the information provided by several positioning sources S1 , S2 , ... , Sn. The advantage of the present disclosure with respect to prior methods is that, by using the information contained in the estimation residuals from each positioning source, the computed protection level is smaller than the protection level that would have been obtained by using the position estimate of each positioning source directly.

The disclosure refers to a system and method for generating trajectories for a robot. The method comprises receiving multidimensional trajectory data, the trajectory data being relative to a plurality of trajectories and comprising a set of points wherein each point is defined by a set of magnitudes, the magnitudes being a position, a velocity and at least one additional parameter. The method further comprises, for each trajectory, normalizing the trajectory data by magnitudes; sampling the normalized trajectory data by applying a multi-dimensional simplification algorithm; discretizing the sampled trajectory data according to a predefined resolution; encoding the discretized data in the form of a codebook; feeding a Hidden Markov Model with the coded trajectory data corresponding to each trajectory; and generating, by the Hidden Markov Model, a set of predicted states to be decoded, within the range of each data magnitude, into a proposed trajectory for the robot.

A computer-implemented method comprising: determining, in an Al system comprising a deep learning model with a plurality of layers defining a weight matrix of the model, groups of two or more contiguous layers in the plurality of layers; for each determined group of two or more contiguous layers, applying SVD to weights of one layer of the group; for each layer with SVD applied thereto, truncating at least some singular values obtained from the application of the SVD based on at least one truncation criterion; for each determined group of two or more contiguous layers, selecting a plurality of output channels of the deep learning model for removal based on at least one weight importance criterion; and for each determined group of two or more contiguous layers, removing one or more input channels and/or one or more output channels based on the selected plurality of output channels such that a shared dimension size in the group is maintained. Also, an apparatus and a computer program.

A method for completion of intra-orally scanned denture. The method includes providing at least one boundary between gingiva and crown faces by processing a mesh representing at least part of segmented teeth and segmented gingiva of a person. The method also includes providing each tooth of the person with a complete crown boundary by determining at least part of a boundary between each tooth and the gingiva and identifying whether there is at least one occluded and/or missing surface with part of a boundary between the tooth and the gingiva missing, and estimating the part of the missing boundary. The method also includes providing a mesh for each tooth of the person based on both faces of the crown thereof and the complete crown boundary thereof.

The disclosure refers to a method and system for measuring optical spectra of signals based on optical spectroscopy. The system comprises a tunable optical source that generates a probe signal, a first optical splitting device that receives a signal under test whose optical spectrum is to be measured, a first optical fiber connected to the first optical splitting device and to the tunable optical source and a first photodetector. The first photodetector is configured to measure, with the signal under test being injected into to the first optical fiber, the insertion losses in the probe signal after having passed through the first optical fiber, subtract a baseline from the measured optical spectrum of the signal under test obtaining a processed optical spectrum and calibrate the processed optical spectrum to obtain the optical spectrum of the signal under test.

A method comprising: processing an instruction to modify a trained artificial intelligence, AI, system, the AI system being configured to provide at least one output based on an input dataset, the trained AI system having the form of a tensor network, the instruction comprising adding a first dataset in the AI system and/or removing a second dataset from the AI system; and running the instruction on the trained AI system, which comprises: when the instruction at least comprises adding the first dataset, encoding data values of the first dataset in one or more tensors of the trained AI system associated with values of the first dataset; and when the instruction at least comprises removing the second dataset, setting to zero values associated with data values or relationships of the second dataset in one or more tensors of the trained AI system associated with values of the second dataset, or removing the one or more tensors associated with values of the second dataset from the AI system. Also, an apparatus, a system and a computer program associated with the method.

A computer-implemented method for simulating and analyzing material deformations with principles of linear elasticity; the method includes: decomposition of a geometry into multiple simple domains and computing mesh-grid tensor as TN-vectors for all dimensions for specifying the corresponding coordinate with defining mesh-grid function for any given input in mesh-grid tensors; using mesh-grid tensors for each simple domains that defined for all available dimensions; computing the components of the Jacobian and determinant of the Jacobian of the element transformation and mapping the reference element into small element of each simple domain to compute them all at once with using TN-operations; processing stress and strain fields within the material, forces applied to the material and test function equations that defined on the storage medium over local elements for the stiffness and mass matrices through the Jacobian components that computed in a previous step; assembling the stiffness TN-operators and the mass TN-operators for each simple domain; stitching the stiffness TN-operators and the mass TN-operators together for enforcing continuity over interfaces; applying mass TN-operator unit to external force TN-vector.

A method comprising: digitally processing a plurality of RFID data transmissions received by at least one antenna assembly, each RFID data transmission having a same identifier, and comprising estimating a location of an RFID tag corresponding to the identifier of the plurality of RFID data transmissions at least based on: a location of a first antenna assembly receiving two or more first RFID data transmissions; and an orientation of a rotary antenna of the first antenna assembly when each of the two or more first RFID data transmissions were received by said rotary antenna; and estimating of the location of the RFID tag comprises obtaining the estimated location of the RFID tag at least based on an average of a number of RFID data transmissions per orientation of the rotary antenna receiving the two or more first RFID data transmissions. Also, a system, and a computing device or system.

A computer-implemented method comprising: controlling at least one light source to emit at least one light beam; controlling at least one mirror to scan the at least one light beam in a first direction; and controlling a microelectromechanical system, MEMS, mirror that the at least one light beam impinges on and directs towards the at least one mirror, wherein the MEMS mirror is controlled to modify how the at least one light beam impinges on the at least one mirror to further scan the at least one light beam in at least a second direction not parallel to the first direction. Also, an apparatus and a method.