4 accepted papers
Tactile sensors have long been valued for their perceptual capabilities, offering rich insights into the otherwise hidden interface between the robot and grasped objects. Yet their inherent compliance—a key driver of force-rich interactions—remains underexplored. The central challenge is to capture …
This paper develop a scheduling protocol for a team of autonomous robots that operate on long-term persistent tasks. The proposed framework, called meSch, accounts for the limited battery capacity of the robots and ensures that the robots return to charge their batteries one at a time at the single
In the last few years, many deep learning (DL) models have been developed to improve the accuracy of speech emotion recognition (SER). However, as SER datasets are generally small and insufficient due to their difficult and expensive collection, the DL models are prone to overfitting, so their perfo…
This paper develops a deep learning model, called Encoder-Recurrent Decoder Network (ERDN), which recovers the clear image from a degrade hazy image without using the atmospheric scattering model. The proposed model consists of two key components- an encoder and a decoder. The encoder is constructed…