I-Support: A robotic platform of an assistive bathing robot for the elderly population

In this paper we present a prototype integrated robotic system, the I-Support bathing robot, that aims at supporting new aspects of assisted daily-living activities on a real-life scenario. The paper focuses on describing and evaluating key novel technological features of the system, with the emphasis on cognitive human–robot interaction modules and their evaluation through a series of clinical validation studies. The I-Support project on its whole has envisioned the development of an innovative, modular, ICT-supported service robotic system that assists frail seniors to safely and independently complete an entire sequence of physically and cognitively demanding bathing tasks, such as properly washing their back and their lower limbs. A variety of innovative technologies have been researched and a set of advanced modules of sensing, cognition, actuation and control have been developed and seamlessly integrated to enable the system to adapt to the target population abilities. These technologies include: human activity monitoring and recognition, adaptation of a motorized chair for safe transfer of the elderly in and out the bathing cabin, a context awareness system that provides full environmental awareness, as well as a prototype soft robotic arm and a set of user-adaptive robot motion planning and control algorithms. This paper focuses in particular on the multimodal action recognition system, developed to monitor, analyze and predict user actions with a high level of accuracy and detail in real-time, which are then interpreted as robotic tasks. In the same framework, the analysis of human actions that have become available through the project’s multimodal audio–gestural dataset, has led to the successful modeling of Human–Robot Communication, achieving an effective and natural interaction between users and the assistive robotic platform. In order to evaluate the I-Support system, two multinational validation studies were conducted under realistic operating conditions in two clinical pilot sites. Some of the findings of these studies are presented and analyzed in the paper, showing good results in terms of: (i) high acceptability regarding the system usability by this particularly challenging target group, the elderly end-users, and (ii) overall task effectiveness of the system in different operating modes

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p

Path Planning and Control of a Cooperative Three-Robot System Manipulating Large Objects

Abstract. After a brief review of the current research on multi-robot systems, the paper presents a path planning and control scheme for a cooperative three-robot system transferring/manipulating a large object from an initial to a desired final position/orientation. The robots are assumed to be capable of holding the object at three points that define an isosceles triangle. The mode of operation adopted is that of a “master-and-two-slave robots”. The control scheme employs the differential displacement of the object which is transformed into that of the end-effector of each robotic arm, and then used to compute the differential displacements of the joints of the robots. The scheme was applied to several 3-robot systems by simulation and proved to be adequately effective, subject to certain conditions regarding the magnitude of the differential displacements. Here, an example is included which concerns the case of three Stäubli RX-90L robots. Key words: multi-robot systems, cooperative three-robot system, path planning-control, master-and-two-slaves mode, large object manipulation

A differential motion planning algorithm for controlling multi-robot systems handling a common object

Multi-robot systems have substantially increased capabilities over single-robot systems and can handle very large or peculiar objects. This paper presents a differential (incremental) motion planning algorithm for an m-robot system (m >or=2) to cooperatively transfer an object from an initial to a desired final position / orientation by rigidly holding it at given respective points Q[sub 1], Q[sub 2],..., Q[sub m]. One of the robots plays the role of a "master" while other robots operate in the "slave" mode maintaining invariant their relative positions and orientations during the system motion. The method employs the differential displacements of the end-effector of each robot arm. Then, the differential displacements of the joints of the m robots are computed for the application of incremental motion control. The algorithm was tested on many examples. A representative of them is shown here, concerning the case of three STAUBLI RX-90L robots similar to 6-dof PUMA robots. The results obtained show the practicality and effectiveness of the method, which, however, needs particular care for completely eliminating the cumulative errors that may occur