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This paper proposes a novel technique for the real-time estimation of the joint torques variations in humans while performing heavy manipulation tasks. To achieve this, the method is based on the deviations of the Centre of Pressure (CoP) and Ground Reaction Force (GRF) in the presence of interaction forces. The CoP and GRF variations are calculated from the difference between the estimated values...
The development of dynamical prosthesis can be considered as an effort of the bioengineering to substitute the functions of the member affected by an amputation. The performance of these devices is strictly related with its control system. In this way, this work aims proposinga control architecture for transfemoral prosthesis, based on the complementary limb motion estimation, considering the hypothesis...
Utilizing the time differences of arrival of a signal, impinging on a distributed sensor network, is a well known approach for the location estimation of a radio wave emitter. The high sampling rate necessary for a precise positioning implies a huge amount of data exchange between the sensor nodes. Contrary, the absence of high data rate enabled backbone links, connecting the nodes, restricts the...
With their greatly reduced sizes, low development cost and rapid construction times, CubeSats have emerged as a platform of intense interest for a wide range of applications, including remote sensing. However, due to their compact form factor, performance tradeoffs relative to larger existing platforms have been encountered. Of specific interest in this paper are data processing challenges associated...
We propose a novel joint registration and segmentation approach to estimate scene flow from RGB-D images. Instead of assuming the scene to be composed of a number of independent rigidly-moving parts, we use non-binary labels to capture non-rigid deformations at transitions between the rigid parts of the scene. Thus, the velocity of any point can be computed as a linear combination (interpolation)...
Attenuation correction is critical to accurate PET quantitation. However, it is challenging to extract accurate attenuation from MR data because of distinct physics of MR and PET. The goal of this study is to achieve robust and accurate attenuation correction in PET/MR. We combine an MR-segmentation based approach and a joint estimation approach synergistically by using an MR-segmentation based attenuation...
This paper proposes a solution for the problem of determination, separation, and tracking of an unknown time-varying number of maneuvering sources based on a mixture of signals received by some omnidirectional sensors located at different places. To our knowledge, this problem has not been addressed in its full range: what has been addressed is limited to some simplified versions (e.g., with a fixed...
Track-to-track association and sensor bias estimation are two important problems in multi-target multi-sensor tracking system. Track-to-track association becomes more complex in the presence of sensor bias and incorrect track association will lead to poor bias estimation results. Solving these two problems jointly would be attractive. This paper proposes a recursive joint track-to-track association...
In joint tracking and classification (JTC) problems, both decision and estimation are involved and they affect each other. Good solutions for JTC require solving the two problems jointly. A joint decision and estimation (JDE) framework based on a generalized Bayes risk was recently proposed for solving the problem of inter-dependent decision and estimation. In the JDE framework, a conditional JDE...
This paper presents a distributed online method for joint state and parameter estimation in a Jump Markov NonLinear System based on a distributed recursive Expectation Maximization algorithm. State inference is enabled via the use of Rao-Blackwellized Particle Filter and, for the parameter estimation, the E-step is performed independently at each sensor with the calculation of local sufficient statistics...
Robot interaction with the environment is normally described as a mass-spring-damping impedance model and the estimation of such interaction impedance parameters requires the computation of the joint (or task) space velocity and acceleration. In many cases, the velocity and acceleration are computed by numerically computing the first and second derivatives of the sensed position signal. The numerical...
Solution of the differential inverse positioning sub-task is an important problem in robotics, that is burdened with kinematic singularities. This problem can be handled by regularizing the task Jacobian, however this requires the knowledge of the regularization vector. A candidate for the regularization vector for an elbow manipulator is given, and it is proved that this candidate can be used in...
Multiple Sclerosis (MS) is an auto-immune, inflammatory disease of the Central Nervous System (CNS), consisting in the progressive demyelinization of axonal fibers. Given its degenerative nature, MS treatment faces complex challenges for both pharmaceutical and therapeutic interventions. Indeed, patients with diagnostic of multiple sclerosis will require continuous rehabilitation for life in order...
In this paper we present a real-time optimal control scheme of a Pendubot based on nonlinear model predictive control (NMPC) combined with nonlinear moving horizon estimation (NMHE). For the control of this fast, under-actuated nonlinear mechatronic system we utilize the ACADO Code Generation tool to obtain a highly efficient Gauss-Newton real-time iteration algorithm tailored for solving the underlying...
People with muscular weakness can benefit from arm supports that compensate the weight of their arms. Due to the disuse of the arms, passive joint stiffness increases and providing only gravity compensation becomes insufficient to support the arm function. Hence, joint stiffness compensation is also required, for which the use of active arm supports is essential. Force-based control interfaces are...
There is a recent increase in development of compact soft wearable robotic devices that are used for rehabilitation and assistance of the hand. In order to rehabilitate or assist natural grasp tasks, the device requires monitoring of hand posture including finger and thumb joint angles. For estimating the finger and thumb joint angles without making the device bulky, bending sensors enable compact...
We considered the new quasi-likelihood amplitude estimate algorithm for the ultra wide band quasi radio signal with unknown initial phase and inaccurately known duration against white Gaussian noise. Its block diagram was presented in single-channel units. We found the statistical characteristics of the introduced estimate and we also investigated the influence of the prior signal duration ignorance...
The Inertial Measurement Units (IMUs) have been widely used equipment to measure different parameters during human locomotion. However, the research gap lies in implementing the IMUs to monitor lower limb joint kinematics. This paper presents a novel approach to estimate the lower limb joint angles using only 4 IMUs attached to the heel and pelvis. We model the gait as a planar 3R (R denotes revolute)...
Canonical correlation analysis (CCA) is an established multivariate statistical method for finding similarities between linear combinations of (normally two) sets of multivariate observations. In this contribution we replace (linear) correlation as the measure of association between the linear combinations with the information theoretical measure mutual information (MI). We term this type of analysis...
In this paper, individual muscular forces of the lower limb are estimated in real-time by inverse dynamics-based static optimization with a wearable sensor system. The wearable sensor system consists of inertial measurement units (IMUs) and manually developed ground reaction force (GRF) sensors. Joint torques of the lower limb during walking are calculated in real-time by applying inverse dynamics...
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