Deep Haptic Model Predictive Control for Robot-Assisted Dressing

Robot-assisted dressing offers an opportunity to benefit the lives of many people with disabilities, such as some older adults. However, robots currently lack common sense about the physical implications of their actions on people. The physical implications of dressing are complicated by non-rigid garments, which can result in a robot indirectly applying high forces to a person's body. We present a deep recurrent model that, when given a proposed action by the robot, predicts the forces a garment will apply to a person's body. We also show that a robot can provide better dressing assistance by using this model with model predictive control. The predictions made by our model only use haptic and kinematic observations from the robot's end effector, which are readily attainable. Collecting training data from real world physical human-robot interaction can be time consuming, costly, and put people at risk. Instead, we train our predictive model using data collected in an entirely self-supervised fashion from a physics-based simulation. We evaluated our approach with a PR2 robot that attempted to pull a hospital gown onto the arms of 10 human participants. With a 0.2s prediction horizon, our controller succeeded at high rates and lowered applied force while navigating the garment around a persons fist and elbow without getting caught. Shorter prediction horizons resulted in significantly reduced performance with the sleeve catching on the participants' fists and elbows, demonstrating the value of our model's predictions. These behaviors of mitigating catches emerged from our deep predictive model and the controller objective function, which primarily penalizes high forces.Comment: 8 pages, 12 figures, 1 table, 2018 IEEE International Conference on Robotics and Automation (ICRA

Transcriptome-based reconstructions from the murine knockout suggest involvement of the urate transporter, URAT1 (slc22a12), in novel metabolic pathways.

URAT1 (slc22a12) was identified as the transporter responsible for renal reabsorption of the medically important compound, uric acid. However, subsequent studies have indicated that other transporters make contributions to this process, and that URAT1 transports other organic anions besides urate (including several in common with the closely related multi-specific renal organic anion transporters, OAT1 (slc22a6) and OAT3 (slc22a8)). These findings raise the possibility that urate transport is not the sole physiological function of URAT1. We previously characterized mice null for the murine ortholog of URAT1 (mURAT1; previously cloned as RST), finding a relatively modest decrement in urate reabsorptive capacity. Nevertheless, there were shifts in the plasma and urinary concentrations of multiple small molecules, suggesting significant metabolic changes in the knockouts. Although these molecules remain unidentified, here we have computationally delineated the biochemical networks consistent with transcriptomic data from the null mice. These analyses suggest alterations in the handling of not only urate but also other putative URAT1 substrates comprising intermediates in nucleotide, carbohydrate, and steroid metabolism. Moreover, the analyses indicate changes in multiple other pathways, including those relating to the metabolism of glycosaminoglycans, methionine, and coenzyme A, possibly reflecting downstream effects of URAT1 loss. Taken together with the available substrate and metabolomic data for the other OATs, our findings suggest that the transport and biochemical functions of URAT1 overlap those of OAT1 and OAT3, and could contribute to our understanding of the relationship between uric acid and the various metabolic disorders to which it has been linked

Multidimensional Capacitive Sensing for Robot-Assisted Dressing and Bathing

Robotic assistance presents an opportunity to benefit the lives of many people with physical disabilities, yet accurately sensing the human body and tracking human motion remain difficult for robots. We present a multidimensional capacitive sensing technique that estimates the local pose of a human limb in real time. A key benefit of this sensing method is that it can sense the limb through opaque materials, including fabrics and wet cloth. Our method uses a multielectrode capacitive sensor mounted to a robot's end effector. A neural network model estimates the position of the closest point on a person's limb and the orientation of the limb's central axis relative to the sensor's frame of reference. These pose estimates enable the robot to move its end effector with respect to the limb using feedback control. We demonstrate that a PR2 robot can use this approach with a custom six electrode capacitive sensor to assist with two activities of daily living-dressing and bathing. The robot pulled the sleeve of a hospital gown onto able-bodied participants' right arms, while tracking human motion. When assisting with bathing, the robot moved a soft wet washcloth to follow the contours of able-bodied participants' limbs, cleaning their surfaces. Overall, we found that multidimensional capacitive sensing presents a promising approach for robots to sense and track the human body during assistive tasks that require physical human-robot interaction.Comment: 8 pages, 16 figures, International Conference on Rehabilitation Robotics 201

Evidence of Environmental Quenching at Redshift z ~ 2

We report evidence of environmental quenching among galaxies at redshift ~ 2, namely the probability that a galaxy quenches its star formation activity is enhanced in the regions of space in proximity of other quenched, more massive galaxies. The effect is observed as strong clustering of quiescent galaxies around quiescent galaxies on angular scales \theta < 20 arcsec, corresponding to a proper(comoving) scale of 168 (502) kpc at z = 2. The effect is observed only for quiescent galaxies around other quiescent galaxies; the probability to find star-forming galaxies around quiescent or around star-forming ones is consistent with the clustering strength of galaxies of the same mass and at the same redshift, as observed in dedicated studies of galaxy clustering. The effect is mass dependent in the sense that the quenching probability is stronger for galaxies of smaller mass ($\rm{M_*<10^{10} Msun}$) than for more massive ones, i.e. it follows the opposite trend with mass relative to gravitational galaxy clustering. The spatial scale where the effect is observed suggests these environments are massive halos, in which case the observed effect would likely be satellite quenching. The effect is also redshift dependent in that the clustering strength of quiescent galaxies around other quiescent galaxies at z = 1.6 is ~ 1.7 times larger than that of the galaxies with the same stellar mass at z = 2.6. This redshift dependence allows for a crude estimate of the time scale of environmental quenching of low-mass galaxies, which is in the range 1.5 - 4 Gyr, in broad agreement with other estimates and with our ideas on satellite quenching.Comment: 12 pages, 9 figures, Accepted for publication in Ap

In situ GISAXS study of the growth of Pd on MgO(001)

The morphology of growing Pd nano-particles on MgO(001) surfaces have been investigated in situ, during growth, by grazing incidence small angle x-ray scattering, for different substrate temperatures. The 2D patterns obtained are quantitatively analyzed, and the average morphological parameters (shape, size) deduced. Above 650 K, the aggregates adopt their equilibrium shape of truncated octahedron, and the interfacial energy is deduced.Comment: 10 pages, 1 Table, 2 Figure

Atomic ionization by sterile-to-active neutrino conversion and constraints on dark matter sterile neutrinos with germanium detectors

The transition magnetic moment of a sterile-to-active neutrino conversion gives rise to not only radiative decay of a sterile neutrino, but also its non-standard interaction (NSI) with matter. For sterile neutrinos of keV-mass as dark matter candidates, their decay signals are actively searched for in cosmic X-ray spectra. In this work, we consider the NSI that leads to atomic ionization, which can be detected by direct dark matter experiments. It is found that this inelastic scattering process for a nonrelativistic sterile neutrino has a pronounced enhancement in the differential cross section at energy transfer about half of its mass, manifesting experimentally as peaks in the measurable energy spectra. The enhancement effects gradually smear out as the sterile neutrino becomes relativistic. Using data taken with germanium detectors that have fine energy resolution in keV and sub-keV regimes, constraints on sterile neutrino mass and its transition magnetic moment are derived and compared with those from astrophysical observations