Learning robust policies for object manipulation with robot swarms

Swarm robotics investigates how a large population of robots with simple actuation and limited sensors can collectively solve complex tasks. One particular interesting application with robot swarms is autonomous object assembly. Such tasks have been solved successfully with robot swarms that are controlled by a human operator using a light source. In this paper, we present a method to solve such assembly tasks autonomously based on policy search methods. We split the assembly process in two subtasks: generating a high-level assembly plan and learning a low-level object movement policy. The assembly policy plans the trajectories for each object and the object movement policy controls the trajectory execution. Learning the object movement policy is challenging as it depends on the complex state of the swarm which consists of an individual state for each agent. To approach this problem, we introduce a representation of the swarm which is based on Hilbert space embeddings of distributions. This representation is invariant to the number of agents in the swarm as well as to the allocation of an agent to its position in the swarm. These invariances make the learned policy robust to changes in the swarm and also reduce the search space for the policy search method significantly. We show that the resulting system is able to solve assembly tasks with varying object shapes in multiple simulation scenarios and evaluate the robustness of our representation to changes in the swarm size. Furthermore, we demonstrate that the policies learned in simulation are robust enough to be transferred to real robots

Robust learning of object assembly tasks with an invariant representation of robot swarms

— Swarm robotics investigates how a large population of robots with simple actuation and limited sensors can collectively solve complex tasks. One particular interesting application with robot swarms is autonomous object assembly. Such tasks have been solved successfully with robot swarms that are controlled by a human operator using a light source. In this paper, we present a method to solve such assembly tasks autonomously based on policy search methods. We split the assembly process in two subtasks: generating a high-level assembly plan and learning a low-level object movement policy. The assembly policy plans the trajectories for each object and the object movement policy controls the trajectory execution. Learning the object movement policy is challenging as it depends on the complex state of the swarm which consists of an individual state for each agent. To approach this problem, we introduce a representation of the swarm which is based on Hilbert space embeddings of distributions. This representation is invariant to the number of agents in the swarm as well as to the allocation of an agent to its position in the swarm. These invariances make the learned policy robust to changes in the swarm and also reduce the search space for the policy search method significantly. We show that the resulting system is able to solve assembly tasks with varying object shapes in multiple simulation scenarios and evaluate the robustness of our representation to changes in the swarm size. Furthermore, we demonstrate that the policies learned in simulation are robust enough to be transferred to real robots

Comparing local energy cascade rates in isotropic turbulence using structure function and filtering formulations

Two common definitions of the spatially local rate of kinetic energy cascade at some scale $\ell$ in turbulent flows are (i) the cubic velocity difference term appearing in the generalized Kolmogorov-Hill equation (GKHE) (structure function approach), and (ii) the subfilter-scale energy flux term in the transport equation for subgrid-scale kinetic energy (filtering approach). We perform a comparative study of both quantities based on direct numerical simulation data of isotropic turbulence at Taylor-scale Reynolds number of 1250. While observations of negative subfilter-scale energy flux (backscatter) have in the past led to debates regarding interpretation and relevance of such observations, we argue that the interpretation of the local structure function-based cascade rate definition is unambiguous since it arises from a divergence term in scale space. Conditional averaging is used to explore the relationship between the local cascade rate and the local filtered viscous dissipation rate as well as filtered velocity gradient tensor properties such as its invariants. We find statistically robust evidence of inverse cascade when both the large-scale rotation rate is strong and the large-scale strain rate is weak. Even stronger net inverse cascading is observed in the ``vortex compression'' $R>0$, $Q>0$ quadrant where $R$ and $Q$ are velocity gradient invariants. Qualitatively similar, but quantitatively much weaker trends are observed for the conditionally averaged subfilter scale energy flux. Flow visualizations show consistent trends, namely that spatially the inverse cascade events appear to be located within large-scale vortices, specifically in subregions when $R$ is large

Blended learning for accredited life support courses - A systematic review.

Aim To evaluate the effectiveness on educational and resource outcomes of blended compared to non-blended learning approaches for participants undertaking accredited life support courses. Methods This review was conducted in adherence with PRISMA standards. We searched EMBASE.com (including all journals listed in Medline), CINAHL and Cochrane from 1 January 2000 to 6 August 2021. Randomised and non-randomised studies were eligible for inclusion. Study screening, data extraction, risk of bias assessment (using RoB2 and ROBINS-I tools), and certainty of evidence evaluation (using GRADE) were all independently performed in duplicate. The systematic review was registered with PROSPERO (CRD42022274392). Results From 2,420 studies, we included data from 23 studies covering fourteen basic life support (BLS) with 2,745 participants, eight advanced cardiac life support (ALS) with 33,579 participants, and one Advanced Trauma Life Support (ATLS) with 92 participants. Blended learning is at least as effective as non-blended learning for participant satisfaction, knowledge, skills, and attitudes. There is potential for cost reduction and eventual net profit in using blended learning despite high set up costs. The certainty of evidence was very low due to a high risk of bias and inconsistency. Heterogeneity across studies precluded any meta-analysis. Conclusion Blended learning is at least as effective as non-blended learning for accredited BLS, ALS, and ATLS courses. Blended learning is associated with significant long term cost savings and thus provides a more efficient method of teaching. Further research is needed to investigate specific delivery methods and the effect of blended learning on other accredited life support courses

Aerosol and Surface Contamination of SARS-CoV-2 Observed in Quarantine and Isolation Care

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in Wuhan, China in late 2019, and its resulting coronavirus disease, COVID-19, was declared a pandemic by the World Health Organization on March 11, 2020. The rapid global spread of COVID-19 represents perhaps the most significant public health emergency in a century. As the pandemic progressed, a continued paucity of evidence on routes of SARS-CoV-2 transmission has resulted in shifting infection prevention and control guidelines between classically-defined airborne and droplet precautions. During the initial isolation of 13 individuals with COVID-19 at the University of Nebraska Medical Center, we collected air and surface samples to examine viral shedding from isolated individuals. We detected viral contamination among all samples, supporting the use of airborne isolation precautions when caring for COVID-19 patients

Long-Term Assessment of the Effects of COVID-19 and Isolation Care on Survivor Disability and Anxiety

We conducted an assessment of disability, anxiety, and other life impacts of COVID-19 and isolation care in a unique cohort of individuals. These included both community admissions to a university hospital as well as some of the earliest international aeromedical evacuees. Among an initial 16 COVID-19 survivors that were interviewed 6-12 months following their admission into isolation care, perception of their isolation care experience was related to their reporting of long-term consequences. However, anxiety and disability assessed with standard scores had no relationship with each other. Both capture of the isolation care experience and caution relying on single scoring systems for assessing long-term consequences in survivors are important considerations for on-going and future COVID-19 and other pandemic survivor research

Characterization of Turing diffusion-driven instability on evolving domains

In this paper we establish a general theoretical framework for Turing diffusion-driven instability for reaction-diffusion systems on time-dependent evolving domains. The main result is that Turing diffusion-driven instability for reaction-diffusion systems on evolving domains is characterised by Lyapunov exponents of the evolution family associated with the linearised system (obtained by linearising the original system along a spatially independent solution). This framework allows for the inclusion of the analysis of the long-time behavior of the solutions of reaction-diffusion systems. Applications to two special types of evolving domains are considered: (i) time-dependent domains which evolve to a final limiting fixed domain and (ii) time-dependent domains which are eventually time periodic. Reaction-diffusion systems have been widely proposed as plausible mechanisms for pattern formation in morphogenesis

Bromelain inhibits SARS-CoV-2 infection via targeting ACE-2, TMPRSS2, and spike protein

The new coronavirus, SARS-CoV-2, transmits rapidly from human-to-human resulting in the ongoing pandemic. SARS-CoV-2 infects angiotensin-converting enzyme 2 (ACE-2) expressing lung, heart, kidney, intestine, gall bladder, and testicular tissues of patients, leading to organ failure and sometimes death.1, 2 Currently, COVID-19 patients are treated with different agents, including favilavir, remdesivir, chloroquine, hydroxychloroquine, lopinavir, darunavir, and tocilizumab.3, 4 However, the safety and efficacy of those drugs against COVID-19 still need further confirmation by randomized clinical trials. Hence, there is an emergent need to repurpose the existing drugs or develop new virus-based and host-based antivirals against SARS-CoV-2. Bromelain is a cysteine protease isolated from pineapple stem and is used as a dietary supplement for treating patients with pain, inflammation,5 thrombosis,6 and cancerPeer Reviewe

Cardiopulmonary resuscitation in low-resource settings: a statement by the International Liaison Committee on Resuscitation, supported by the AFEM, EUSEM, IFEM, and IFRC.

Most recommendations on cardiopulmonary resuscitation were developed from the perspective of high-resource settings with the aim of applying them in these settings. These so-called international guidelines are often not applicable in low-resource settings. Organisations including the International Liaison Committee on Resuscitation (ILCOR) have not sufficiently addressed this problem. We formed a collaborative group of experts from various settings including low-income, middle-income, and high-income countries, and conducted a prospective, multiphase consensus process to formulate this ILCOR Task Force statement. We highlight the discrepancy between current cardiopulmonary resuscitation guidelines and their applicability in low-resource settings. Successful existing initiatives such as the Helping Babies Breathe programme and the WHO Emergency Care Systems Framework are acknowledged. The concept of the chainmail of survival as an adaptive approach towards a framework of resuscitation, the potential enablers of and barriers to this framework, and gaps in the knowledge are discussed, focusing on low-resource settings. Action points are proposed, which might be expanded into future recommendations and suggestions, addressing a large diversity of addressees from caregivers to stakeholders. This statement serves as a stepping-stone to developing a truly global approach to guide resuscitation care and science, including in health-care systems worldwide