Robot Interaction Force Estimation Using an Adaptive Sliding Mode Observer

In constrained motion control of a robot,the interaction force is an important variable,which directly describes the state of interaction.It is required in a number of algorithms for interaction control.Desirably,the interaction force has to be measured by force sensors.However,there are inherent limitations with force sensors,such as the cost,sensing noise,limited bandwidth,and the difficulty of physical location at the required place,which is dynamic.In the present paper,the interaction force is estimated by using high order sliding mode observers.An adaptive version of a high order sliding mode observer is developed to robustly reconstruct the interaction force.Experimental results are given to show the effectiveness of the developed algorithms.

Robust Impedance Control of Robots Using an Adaptive Interaction Force Observer

For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type of interaction control.Specifically,in impedance control,the dynamic relationship between the interaction force and the resulting motion is controlled.In order to control the impedance of a mechanical system,typically,the interaction force has to be sensed.Due to the inherent limitations of direct force sensing at the interaction site,in the present work,the interaction force is observed using robust observers.In particular,to enhance the accuracy of impedance control,a first order sliding mode impedance controller is designed and incorporated in the present paper.Its advantage over positionbased interaction control algorithms is demonstrated through experimentation.Experimental results are given to show the effectiveness of the proposed algorithms.

Altered vaginal eukaryotic virome is associated with different cervical disease status

Viruses are important components of the human body.Growing evidence suggests that they are engaged in the physiology and disease status of the host.Even though the vaginal microbiome is involved in human papillomavirus(HPV)infection and cervical cancer(CC)progression,little is known about the role of the vaginal virome.In this pilot exploratory study,using unbiased viral metagenomics,we aim to investigate the vaginal eukaryotic virome in women with different levels of cervical lesions,and examine their associations with different cervical disease status.An altered eukaryotic virome was observed in women with different levels of lesions and Lactobacillus profiles.Anelloviruses and papillomaviruses are the most commonly detected eukaryotic viruses of the vaginal virome.Higher abundance and richness of anelloviruses and papillomaviruses were associated with lowgrade squamous intraepithelial lesion(LSIL)and CC.Besides,higher anellovirus abundance was also associated with lactobacillus-depleted microbiome profiles and bacterial community state(CST)type IV.Furthermore,increased correlations between Anelloviridae and Papillomaviridae occurred in the women with increased cervical disease severity level from LSIL to CC.These data suggest underlying interactions between different microbes as well as the host physiology.Higher abundance and diversity of both anelloviruses and papillomaviruses shared by LSIL and CC suggest that anellovirus may be used as a potential adjunct biomarker to predict the risk of HPV persistent infection and/or CC.Future studies need to focus on the clinical relevance of anellovirus abundance with cervical disease status,and the evaluation of their potential as a new adjunct biomarker for the prediction and prognoses of CC.