RESUMO
Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target's unknown properties across all phases. Centroid and light-curve algorithms estimate the body-spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface.
RESUMO
AIM OF THE STUDY: In a consecutive cohort of cardiac arrest (CA) treated with extracorporeal cardiopulmonary resuscitation (eCPR), we describe the incidence of brain death (BD), the eligibility for organ donation and the short-term follow-up of the transplanted organs. METHODS: All refractory in- and out-of-hospital CA admitted to our Cardiac Intensive Care Unit between January 2011 and September 2016 treated with eCPR were enrolled in the study. RESULTS: 112 CA patients received eCPR. 82 (73.2%) died in hospital, 25 BD (22.3%) and 57 for other causes (50.9%). At the time of first neurological evaluation after rewarming, variables related to evolution to BD were a lower GCS (3 [3-3] vs. 8 [3-11], p<0.001), a higher level of neuron specific enolase (269.3±49.4 vs. 55.2±37.2ng/ml, p<0.001), a higher presence of EEG indices of poor outcome (84% vs. 15%, p<0.001), absence of brainstem reflexes (p<0.001), absence of bilateral N20 SSEPS waves (66.7% vs. 3.7%, p<0.001). None of BD patients present a normal CT scan (at 2.5±2days), with 85% prevalence of diffuse hypoxic injury and a mean grey/white matter ratio of 1.1±0.1. Rate of donation in BD patients was 56%, with 39 donated organs: 23 kidneys, 12 livers, and 4 lungs. 89.74% of the transplanted organs reached an early good functional recovery. CONCLUSION: In refractory CA patients treated with eCPR, the prevalence of BD is high. This population has a high potential for considering organ donation. Donated organs have a good outcome.
