Safe, Scalable, and Complete Motion Planning of Large Teams of Interchangeable Robots

Large teams of mobile robots have an unprecedented potential to assist humans in a number of roles ranging from humanitarian efforts to e-commerce order fulfillment. Utilizing a team of robots provides an inherent parallelism in computation and task completion while providing redundancy to isolated robot failures. Whether a mission requires all robots to stay close to each other in a formation, navigate to a preselected set of goal locations, or to actively try to spread out to gain as much information as possible, the team must be able to successfully navigate the robots to desired locations. While there is a rich literature on motion planning for teams of robots, the problem is sufficiently challenging that in general all methods trade off one of the following properties: completeness, computational scalability, safety, or optimality. This dissertation proposes robot interchangeability as an additional trade-off consideration. Specifically, the work presented here leverages the total interchangeability of robots and develops a series of novel, complete, computationally tractable algorithms to control a team of robots and avoid collisions while retaining a notion of optimality. This dissertation begins by presenting a robust decentralized formation control algorithm for control of robots operating in tight proximity to one another. Next, a series of complete, computationally tractable multiple robot planning algorithms are presented. These planners preserve optimality, completeness, and computationally tractability by leveraging robot interchangeability. Finally, a polynomial time approximation algorithm is proposed that routes teams of robots to visit a large number of specified locations while bounding the suboptimality of total mission completion time. Each algorithm is verified in simulation and when applicable, on a team of dynamic aerial robots

Advances in Civic Co-management within the Geospatial Ecosystem Applied to Disaster Risk Management

The use of mobile devices for identifying risk and coordinating disaster response is well accepted and has been proven as a critical element in disaster risk management. As new tools, applications, and software are adopted by municipal governments and NGOs for the identification and management of urban risk, the need for greater integration of the various data they collect becomes acute. While the challenge of integrated data management is substantial, it is aided by the fact that many new tools have been developed to include an Application Programming Interface (API), which allows the machine-to-machine (i.e. automated) sharing of open data. While some proprietary platforms for the management of urban data are currently available, they are extremely costly and very limited in terms of data inputs; to date there are no open source geospatial software tools for the integrated management of various API sources to evaluate hazards for disaster response. A key to improving disaster risk management as an element of risk identification is the development of an integrated open source Decision-Support Risk Evaluation Matrix that enables: 1) automated integration of multiple geospatial and non-geosapatial API sources into a low cost, user-oriented dashboard; 2) backend database and software design for the Risk Evaluation Matrix that enables data sources to be parameterized and interrogated; 3) the development of an output API stream that allows additional secondary applications to optimize their evaluations and analyses through open access to critical risk information. To address these challenges this paper presents an open source Risk Evaluation Matrix, currently in development, which aims to provide situational oversight of flood hazards from multiple data-sources, including social media, in the city of Jakarta, Indonesia

Counting the bodies: Estimating the numbers and spatial variation of Australian reptiles, birds and mammals killed by two invasive mesopredators

Aim Introduced predators negatively impact biodiversity globally, with insular fauna often most severely affected. Here, we assess spatial variation in the number of terrestrial vertebrates (excluding amphibians) killed by two mammalian mesopredators introduced to Australia, the red fox (Vulpes vulpes) and feral cat (Felis catus). We aim to identify prey groups that suffer especially high rates of predation, and regions where losses to foxes and/or cats are most substantial. Location Australia. Methods We draw information on the spatial variation in tallies of reptiles, birds and mammals killed by cats in Australia from published studies. We derive tallies for fox predation by (i) modelling continental-scale spatial variation in fox density, (ii) modelling spatial variation in the frequency of occurrence of prey groups in fox diet, (iii) analysing the number of prey individuals within dietary samples and (iv) discounting animals taken as carrion. We derive point estimates of the numbers of individuals killed annually by foxes and by cats and map spatial variation in these tallies. Results Foxes kill more reptiles, birds and mammals (peaking at 1071 km−2 year−1) than cats (55 km−2 year−1) across most of the unmodified temperate and forested areas of mainland Australia, reflecting the generally higher density of foxes than cats in these environments. However, across most of the continent – mainly the arid central and tropical northern regions (and on most Australian islands) – cats kill more animals than foxes. We estimate that foxes and cats together kill 697 million reptiles annually in Australia, 510 million birds and 1435 million mammals. Main conclusions This continental-scale analysis demonstrates that predation by two introduced species takes a substantial and ongoing toll on Australian reptiles, birds and mammals. Continuing population declines and potential extinctions of some of these species threatens to further compound Australia's poor contemporary conservation record

Muscle-Specific Adaptations, Impaired Oxidative Capacity and Maintenance of Contractile Function Characterize Diet-Induced Obese Mouse Skeletal Muscle

BACKGROUND:The effects of diet-induced obesity on skeletal muscle function are largely unknown, particularly as it relates to changes in oxidative metabolism and morphology. PRINCIPAL FINDINGS:Compared to control fed mice, mice fed a high fat diet (HFD; 60% kcal: fat) for 8 weeks displayed increased body mass and insulin resistance without overt fasting hyperglycemia (i.e. pre-diabetic). Histological analysis revealed a greater oxidative potential in the HFD gastrocnemius/plantaris (increased IIA, reduced IIB fiber-type percentages) and soleus (increased I, IIA cross-sectional areas) muscles, but no change in fiber type percentages in tibialis anterior muscles compared to controls. Intramyocellular lipid levels were significantly increased relative to control in HFD gastrocnemius/plantaris, but were similar to control values in the HFD soleus. Using a novel, single muscle fiber approach, impairments in complete palmitate and glucose oxidation (72.8+/-6.6% and 61.8+/-9.1% of control, respectively; p<0.05) with HFD were detected. These reductions were consistent with measures made using intact extensor digitorum longus and soleus muscles. Compared to controls, no difference in succinate dehydrogenase or citrate synthase enzyme activities were observed between groups in any muscle studied, however, short-chain fatty acyl CoA dehydrogenase (SCHAD) activity was elevated in the HFD soleus, but not tibialis anterior muscles. Despite these morphological and metabolic alterations, no significant difference in peak tetanic force or low-frequency fatigue rates were observed between groups. CONCLUSIONS:These findings indicate that HFD induces early adaptive responses that occur in a muscle-specific pattern, but are insufficient to prevent impairments in oxidative metabolism with continued high-fat feeding. Moreover, the morphological and metabolic changes which occur with 8 weeks of HFD do not significantly impact muscle contractile properties

Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative

Abstract Background In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Results Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. Conclusion We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed

Meta-analysis of human genome-microbiome association studies: The MiBioGen consortium initiative

Background: In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Results: Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. Conclusion: We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed

Safe, scalable, and complete motion planning of large teams of interchangeable robots

Large teams of mobile robots have an unprecedented potential to assist humans in a number of roles ranging from humanitarian efforts to e-commerce order fulfillment. Utilizing a team of robots provides an inherent parallelism in computation and task completion while providing redundancy to isolated robot failures. Whether a mission requires all robots to stay close to each other in a formation, navigate to a preselected set of goal locations, or to actively try to spread out to gain as much information as possible, the team must be able to successfully navigate the robots to desired locations. While there is a rich literature on motion planning for teams of robots, the problem is sufficiently challenging that in general all methods trade off one of the following properties: completeness, computational scalability, safety, or optimality. This dissertation proposes robot interchangeability as an additional trade-off consideration. Specifically, the work presented here leverages the total interchangeability of robots and develops a series of novel, complete, computationally tractable algorithms to control a team of robots and avoid collisions while retaining a notion of optimality. This dissertation begins by presenting a robust decentralized formation control algorithm for control of robots operating in tight proximity to one another. Next, a series of complete, computationally tractable multiple robot planning algorithms are presented. These planners preserve optimality, completeness, and computationally tractability by leveraging robot interchangeability. Finally, a polynomial time approximation algorithm is proposed that routes teams of robots to visit a large number of specified locations while bounding the suboptimality of total mission completion time. Each algorithm is verified in simulation and when applicable, on a team of dynamic aerial robots

Trajectory Design and Control for Aggressive Formation Flight with Quadrotors

Abstract In this work we consider the problem of controlling a team of microaerial vehicles moving quickly through a three-dimensional environment while maintaining a tight formation. The formation is specified by a shape matrix that prescribes the relative separations and bearings between the robots. Each robot plans its trajectory independently based on its local information of other robot plans and estimates of states of other robots in the team to maintain the desired shape. We explore the interaction between nonlinear decentralized controllers, the fourth-order dynamics of the individual robots, the time delays in the network, and the effects of communication failures on system performance. An experimental evaluation of our approach on a team of quadrotors suggests that suitable performance is maintained as the formation motions become increasingly aggressive and as communication degrades

Ecosystem Services and Marine Planning in Gwaii Haanas, Haida Gwaii

Abstract—This paper presents a computationally tractable, resolution-complete algorithm for generating dynamically feasible trajectories for N interchangeable (identical) aerial robots navigating through cluttered known environments to M goal states. This is achieved by assigning the robots to goal states while concurrently planning the trajectories for all robots. The algorithm minimizes the maximum cost over all robot trajectories. The computational complexity of this algorithm is shown to be cubic in the number of robots, substantially better than the expected exponential complexity associated with planning in the joint state space and the assignment of goals to robots. This algorithm can be used to plan motions and goals for tens of aerial robots, each in a 12-dimensional state space. Finally, experimental trials are conducted with a team of six quadrotor robots navigating in a constrained three-dimensional environment. I