We consider the optimal power scheduling problem for the decentralized estimation of a noise-corrupted deterministic signal in an inhomogeneous sensor network. Sensor observations are first quantized into discrete messages, then transmitted to a fusion center where a final estimate is generated. Supposing that the sensors use a universal decentralized quantization/estimation scheme and an uncod...

In this paper, a new formulation along with numerical solution for the problem of finding a point-to-point trajectory with maximum load carrying capacities for flexible manipulators is proposed. For rigid manipulators, the major limiting factor in determining the Dynamic Load Carrying Capacity (DLCC) is the joint actuator capacity. The flexibility exhibited by light weight robots or by robots o...

The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay constraint. It is shown that, under the mean-square error distortion metric, an optimal encoder-decoder pair from the linear and time-invariant (LTI) class can be fou...

In this paper, recurrent neural network is used for path planning in the joint space of the robot with obstacle in the workspace of the robot. To design the neural network, first a performance index has been defined as sum of square of error tracking of final executor. Then, obstacle avoidance scheme is presented based on its space coordinate and its minimum distance between the obstacle and ea...

Modeling realistic human joint limits is important for applications involving physical human-robot interaction. However, setting appropriate human joint limits is challenging because it is pose-dependent: the range of joint motion varies depending on the positions of other bones. The paper introduces a new technique to accurately simulate human joint limits in physics simulation. We propose to ...

While agreement-based joint training has proven to deliver state-of-the-art alignment accuracy, the produced word alignments are usually restricted to one-toone mappings because of the hard constraint on agreement. We propose a general framework to allow for arbitrary loss functions that measure the disagreement between asymmetric alignments. The loss functions can not only be defined between a...

This paper proposes a reduced-rank scheme for adaptive beamforming based on the constrained joint iterative optimization of filters. We employ this scheme to devise two novel reduced-rank adaptive algorithms according to the constant modulus (CM) criterion with different constraints. The first devised algorithm is formulated as a constrained joint iterative optimization of a projection matrix a...