A Fast Score-Based Method for Robotic Task-Free Point-to-Point Path Learning

The manipulation of deformable objects represents an open research topic because of the difficulties in accurately modeling the object behavior in real-world scenarios. This paper presents a trajectory planning framework for the assembly of wiring harnesses for the automotive and aerospace sector, reducing the learning time and simultaneously presenting suitable performance and reliability. A genetic algorithm is used to generate new trajectories according to application constraints. Those trajectories are then executed by the robot and evaluated by means of proper sensor feedback. The proposed framework enable to learn and autonomously improve the task execution, while mantaining a significantly low programming time. Experimental results are reported showing how the robot is capable of optimizing the manipulation of the DLOs gaining experience along the task repetition, while showing high success rate from the very beginning of the learning phase

Cable Detection and Manipulation for DLO-in-Hole Assembly Tasks

This paper describes a cyber-physical system for the manipulation of Deformable Linear Objects (DLOs) addressing the DLO-in-hole insertion problem targeting an industrial sce-nario, the switchgear's components cabling task. In particular, the task considered is the insertion of DLOs in the switchgear components' holes. This task is very challenging since a precise knowledge of the DLO tip position and orientation is required for a successful operation. We tackled the DLO-in-hole problem from the computer vision perspective constraining our setup on employing just simple 2D images and by using the mobility of the robotic arm for achieving the full 3D knowledge of the DLOs. Then, the DLO tip is detected from two different image planes and the robot's trajectory corrected accordingly before insertion. To prove the effectiveness of the proposed solution, an example scenario is prepared and the method validated experimentally attempting the insertion of several DLOs in a sample switchgear component, obtaining an overall insertion success rate of 82.5 %

Deformable Linear Objects 3D Shape Estimation and Tracking From Multiple 2D Views

This letter presents DLO3DS , an approach for the 3D shapes estimation and tracking of Deformable Linear Objects (DLOs) such as cables, wires or plastic hoses, using a cheap and compact 2D vision sensor mounted on the robot end-effector. DLO3DS can be applied in all those scenarios in which the perception and manipulation of DLO-like structures are needed, such as in the case of switchgear cabling, wiring harness manufacturing and assembly in the automotive and aerospace industries, or production of hoses for medical applications. The developed procedure is based on a pipeline that first processes the images coming from the 2D camera extracting key topological points along the DLOs. These points are then used to model each DLO with a B-spline curve. Finally, the set of splines obtained from all the images is matched by exploiting a multi-view stereo-based algorithm. DLO3DS is validated both on a real scenario and on simulated data obtained by exploiting a rendering engine for photo-realistic images. In this way, reliable ground-truth data are retrieved and utilized for assessing the estimation error achievable by DLO3DS , which on the employed test set is characterized by a mean reconstruction error of 0.82 mm

RHESSI Spectral Fits of Swift GRBs

One of the challenges of the Swift era has been accurately determining Epeak for the prompt GRB emission. RHESSI, which is sensitive from 30 keV to 17 MeV, can extend spectral coverage above the Swift-BAT bandpass. Using the public Swift data, we present results of joint spectral fits for 26 bursts co-observed by RHESSI and Swift-BAT through May 2007. We compare these fits to estimates of Epeak which rely on BAT data alone. A Bayesian Epeak estimator gives better correspondence with our measured results than an estimator relying on correlations with the Swift power law indices.Comment: 4 pages, 1 figure. To appear in the proceedings of Gamma Ray Bursts 2007, Santa Fe, New Mexico, November 5-9 200

RT-DLO: Real-Time Deformable Linear Objects Instance Segmentation

Deformable Linear Objects (DLOs) such as cables, wires, ropes, and elastic tubes are numerously present both in domestic and industrial environments. Unfortunately, robotic systems handling DLOs are rare and have limited capabilities due to the challenging nature of perceiving them. Hence, we propose a novel approach named RT-DLO for real-time instance segmentation of DLOs. First, the DLOs are semantically segmented from the background. Afterward, a novel method to separate the DLO instances is applied. It employs the generation of a graph representation of the scene given the semantic mask where the graph nodes are sampled from the DLOs center-lines whereas the graph edges are selected based on topological reasoning. RT-DLO is experimentally evaluated against both DLO-specific and general-purpose instance segmentation deep learning approaches, achieving overall better performances in terms of accuracy and inference time

Electric and hybrid vehicle testing: BMWi3 performance assessment in realistic use scenarios

A plug-in electric vehicle with range extender was tested at ambient temperatures varying between -30°C and 50°C. The objective was to assess energy efficiency variability depending on use conditions. The test campaign was performed in the framework of the transatlantic collaboration between the United States' Department of Energy (Argonne National Laboratory) and the European Commission's Joint Research Centre.JRC.C.4-Sustainable Transpor

HETE-2 Observations of the X-Ray Flash XRF 040916

A long X-ray flash was detected and localized by the instruments aboard the High Energy Transient Explorer II (HETE-2) at 00:03:30 UT on 2004 September 16. The position was reported to the GRB Coordinates Network (GCN) approximately 2 hours after the burst. This burst consists of two peaks separated by 200 s, with durations of 110 s and 60 s. We have analyzed the energy spectra of the 1st and 2nd peaks observed with the Wide Field X-Ray Monitor (WXM) and the French Gamma Telescope (FREGATE). We discuss the origin of the 2nd peak in terms of flux variabilities and timescales. We find that it is most likely part of the prompt emission, and is explained by the long-acting engine model. This feature is similar to some bright X-ray flares detected in the early afterglow phase of bursts observed by the Swift satellite.Comment: 9 pages, 4 figures, Accepted for publication in PAS

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

REMODEL. WP5. T5_5_3. ROSAPP for Deformable Objects Grasping and Shape Detection with Tactile Fingers and Industrial Grippers

The dataset presented by UNIBO consist in two different tests aimed to evaluate the tactile sensor. The experiment consist in the grasping on a DLO (electrical cable) and the correction of robot position using the information from the tactile sensor. In the ‘linear’ experiment the robot move along z. In the ‘angular’ experiment, the robot move along z and correct the orientation of the gripper. In the data are gathered the result, showing the robot position and grasped cable position first order estimation on the sensor before and after the correction