How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations

In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. The robot has to learn the selected path and pass a wire through the peg table by using the same tool. The main contribution regards the hybrid use of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning. Some constraints are introduced to deal with non-rigid material without breaks or knots. We took into account a series of metrics to evaluate the robot learning capabilities, all of them over performed the targets

Fast human motion prediction for human-robot collaboration with wearable interfaces

In this paper, we aim at improving human motion prediction during human-robot collaboration in industrial facilities by exploiting contributions from both physical and physiological signals. Improved human-machine collaboration could prove useful in several areas, while it is crucial for interacting robots to understand human movement as soon as possible to avoid accidents and injuries. In this perspective, we propose a novel human-robot interface capable to anticipate the user intention while performing reaching movements on a working bench in order to plan the action of a collaborative robot. The proposed interface can find many applications in the Industry 4.0 framework, where autonomous and collaborative robots will be an essential part of innovative facilities. A motion intention prediction and a motion direction prediction levels have been developed to improve detection speed and accuracy. A Gaussian Mixture Model (GMM) has been trained with IMU and EMG data following an evidence accumulation approach to predict reaching direction. Novel dynamic stopping criteria have been proposed to flexibly adjust the trade-off between early anticipation and accuracy according to the application. The output of the two predictors has been used as external inputs to a Finite State Machine (FSM) to control the behaviour of a physical robot according to user's action or inaction. Results show that our system outperforms previous methods, achieving a real-time classification accuracy of $94.3\pm2.9\%$ after $160.0msec\pm80.0msec$ from movement onset

Teaching humanoid robotics by means of human teleoperation through RGB-D sensors

This paper presents a graduate course project on humanoid robotics offered by the University of Padova. The target is to safely lift an object by teleoperating a small humanoid. Students have to map human limbs into robot joints, guarantee the robot stability during the motion, and teleoperate the robot to perform the correct movement. We introduce the following innovative aspects with respect to classical robotic classes: i) the use of humanoid robots as teaching tools; ii) the simplification of the stable locomotion problem by exploiting the potential of teleoperation; iii) the adoption of a Project-Based Learning constructivist approach as teaching methodology. The learning objectives of both course and project are introduced and compared with the students\u2019 background. Design and constraints students have to deal with are reported, together with the amount of time they and their instructors dedicated to solve tasks. A set of evaluation results are provided in order to validate the authors\u2019 purpose, including the students\u2019 personal feedback. A discussion about possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels

Quantitative hierarchical representation and comparison of hand grasps from electromyography and kinematic data

Motivation: Modeling human grasping and hand movements is important for robotics, prosthetics and rehabilitation. Several qualitative taxonomies of hand grasps have been proposed in scientific literature. However it is not clear how well they correspond to subjects movements. Objective: In this work we quantitatively analyze the similarity between hand movements in 40 subjects using different features. Methods: Publicly available data from 40 healthy subjects were used for this study. The data include electromyography and kinematic data recorded while the subjects perform 20 hand grasps. The kinematic and myoelectric signal was windowed and several signal features were extracted. Then, for each subject, a set of hierarchical trees was computed for the hand grasps. The obtained results were compared in order to evaluate differences between features and different subjects. Results: The comparison of the signal feature taxonomies revealed a relation among the same subject. The comparison of the subject taxonomies highlighted also a similarity shared between subjects except for rare cases. Conclusions: The results suggest that quantitative hierarchical representations of hand movements can be performed with the proposed approach and the results from different subjects and features can be compared. The presented approach suggests a way to perform a systematic analysis of hand movements and to create a quantitative taxonomy of hand movements

Robot Learning by observing human actions

Nowadays, robotics is entering in our life. One can see robot in industries, offices and even in homes. The more robots are in contact with people, the more requests of new capabilities and new features increase, in order to make robots able to act in case of need, help humans or be a companion. Therefore, it becomes essential to have a quick and easy way to teach new skills to robots. That is the aim of Robot Learning from Demonstration. This paradigm allows to directly program new tasks in a robot through demonstrations. This thesis proposes a novel approach to Robot Learning from Demonstration able to learn new skills from natural demonstrations carried out from naive users. To this aim, we introduce a novel Robot Learning from Demonstration framework by proposing novel approaches in all functional sub-units: from data acquisition to motion elaboration, from information modeling to robot control. A novel method is explained to extract 3D motion flow information from both RGB and depth data acquired by using recently introduced consumer RGB-D cameras. The motion data are computed over the time to recognize and classify human actions. In this thesis, we describe new techniques to remap human motion to robotic joints. Our methods allow people to natural interact with robots by re-targeting the whole body movements in an intuitive way. We develop algorithm for both humanoids and manipulators motion and test them in different situations. Finally, we improve modeling techniques by using a probabilistic method: the Donut Mixture Model. This model is able to manage several interpretations that different people can produce performing a task. The estimated model can also be updated directly by using new attempts carried out by the robot. This feature is very important to rapidly obtain correct robot trajectories by means of few human demonstrations. A further contribution of this thesis is the creation of a number of new virtual models for the different robots we used to test our algorithms. All the developed models are compliant with ROS, so they can be used to foster research in the field from all the community of this very diffuse robotics framework. Moreover, a new 3D dataset is collected to compare different action recognition algorithms. The dataset contains both RGB-D information coming directly from the sensor and skeleton data provided by a skeleton tracker

A quantitative taxonomy of human hand grasps

Background: A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and thus they are usually not quantitatively justified. Methods: This paper presents to the best of our knowledge the first quantitative taxonomy of hand grasps based on biomedical data measurements. The taxonomy is based on electromyography and kinematic data recorded from 40 healthy subjects performing 20 unique hand grasps. For each subject, a set of hierarchical trees are computed for several signal features. Afterwards, the trees are combined, first into modality-specific (i.e. muscular and kinematic) taxonomies of hand grasps and then into a general quantitative taxonomy of hand movements. The modality-specific taxonomies provide similar results despite describing different parameters of hand movements, one being muscular and the other kinematic. Results: The general taxonomy merges the kinematic and muscular description into a comprehensive hierarchical structure. The obtained results clarify what has been proposed in the literature so far and they partially confirm the qualitative parameters used to create previous taxonomies of hand grasps. According to the results, hand movements can be divided into five movement categories defined based on the overall grasp shape, finger positioning and muscular activation. Part of the results appears qualitatively in accordance with previous results describing kinematic hand grasping synergies. Conclusions: The taxonomy of hand grasps proposed in this paper clarifies with quantitative measurements what has been proposed in the field on a qualitative basis, thus having a potential impact on several scientific fields

Topological Sieving of Rings According to Their Rigidity

We present a novel mechanism for resolving the mechanical rigidity of nanoscopic circular polymers that flow in a complex environment. The emergence of a regime of negative differential mobility induced by topological interactions between the rings and the substrate is the key mechanism for selective sieving of circular polymers with distinct flexibilities. A simple model accurately describes the sieving process observed in molecular dynamics simulations and yields experimentally verifiable analytical predictions, which can be used as a reference guide for improving filtration procedures of circular filaments. The <i>topological sieving</i> mechanism we propose ought to be relevant also in probing the microscopic details of complex substrates

Automated and Flexible Coil Winding Robotic Framework

European electrical machines manufacturers need to increase the flexibility of production process, due to the high cost of equipment setup at the beginning of each new production batch. Overall, most of these European manufacturers are striving to reduce costs while preserving the quality of products, in order to face the competition by Far East companies. There is a strong need for increasing productivity, flexibility and quality. In particular, in wound coils manufacturing process, current technologies allow only to big international manufacturer to automate their production lines, due to high machinery cost and set-up time, while small and medium manufacturers are forced to direct themselves towards manual production. This work aims to reduce costs and increase flexibility with the following contributions: (1) important reduction of setup time and costs of the winding machine, thanks to the simplicity and flexibility of the proposed approach; (2) increase in the quality of the final motors, thanks to the increased amount of copper that the robot will be able to insert in each coil with respect to manual winding; (3) possibility to parallelize the winding operations, dramatically increasing production rate; (4) decreased number of defected cores, thanks to an advanced quality inspection system; (5) reduction of environmental impact of the production process, thanks to a reduction of wasted copper wire

Donne immigrate e screening cervicale nel Veneto

According to the literature, women coming from countries with strong migratory pressure are at a greater risk of cancer of the cervix with respect to Italian women. This is connected with the fact that women born outside Italy are less likely to undergo a cervical smear. In the Veneto Region the official immigrant population is equivalent to approximately 10% of the total population. This article analyzes the utilization of cervical smear from immigrant women in the Veneto Region, taking into account the smears performed both inside and outside organized screening programmes. Data have been gathered both from the archives of the screening programmes of the Local Health Authorities and from PASSI, a national surveillance system based on a standardized questionnaire administered through telephone interviews. The screening crude participation rate among foreign women was 45.3%, only slightly lower than the one of Italian women. The participation is lower in women from Asia and in women above 50 years. The percentage of positive smear tests was 2.7% among Italian women and 4.0% among foreign women. Compliance to colposcopy has been 89.9% for Italian women and 88.1% for foreign women. The detection rate of cervical intraepithelial neoplasia grade II or worse (CIN II+ diagnoses) in foreign women has been twofold the one detected in Italian women. If we consider the number of smear tests carried out in the last three years and outside the context of screening programmes, the number of women who have undergone a pap smear is much higher among Italian women, women 39-45 years old and women with a high level of education and without particular economic difficulties. The opposite is true for the organized screening programmes, where the differences according to age, level of education, economic difficulties and citizenship are reduced. These data confirm that women coming from countries with strong migratory pressure are at a greater risk of cancer of the cervix with respect to Italian women. A decrease in inequalities (in terms of education level, socio-economical status and nationality) is shown when considering the access to the screening programs

Congenital aplasia of the optic chiasm and esophageal atresia: a case report

<p>Abstract</p> <p>Introduction</p> <p>The complete absence of the chiasm (chiasmal aplasia) is a rare clinical condition. Hypoplasia of the optic nerve and congenital nystagmus are almost invariably associated characteristics. Microphthalmos or anophthalmos are common features in chiasmal aplasia, while central nervous system abnormalities are less frequent. Esophageal atresia can be isolated or syndromic. In syndromic cases, it is frequently associated with cardiac, limb, renal or vertebral malformations and anal atresia. More rarely, esophageal atresia can be part of anophthalmia-esophageal-genital syndrome, which comprises anophthalmia or microphthalmia, genital abnormalities, vertebral defects and cerebral malformations. Here, a previously unreported case of chiasmal aplasia presenting without microphthalmos and associated with esophageal atresia is described.</p> <p>Case presentation</p> <p>Aplasia of the optic chiasm was identified in a Caucasian Italian 8-month-old boy with esophageal atresia. An ultrasound examination carried out at 21 weeks' gestation revealed polyhydramnios. Intrauterine growth retardation, esophageal atresia and a small atrial-septal defect were subsequently detected at 28 weeks' gestation. Repair of the esophageal atresia was carried out shortly after birth. A jejunostomy was carried out at four months to facilitate enteral feeding. The child was subsequently noted to be visually inattentive and to be neurodevelopmentally delayed. Magnetic resonance imaging revealed chiasmal aplasia. No other midline brain defects were found. His karyotype was normal.</p> <p>Conclusion</p> <p>If achiasmia is a spectrum, our patient seems to depict the most severe form, since he appears to have an extremely severe visual impairment. This is in contrast to most of the cases described in the literature, where patients maintain good--or at least useful-- visual function. To the best of our knowledge, the association of optic nerve hypoplasia, complete chiasmal aplasia, esophageal atresia and atrial-septal defect, choanal atresia, hypertelorism and psychomotor retardation has never been described before.</p