Generating informative paths for persistent sensing in unknown environments

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 127-130).In this thesis, we present an adaptive control law for a team of robots to shape their paths to locally optimal configurations for sensing an unknown dynamical environment. As the robots travels through their paths, they identify the areas where the environment is dynamic and shape their paths to sense these areas. A Lyapunov-like stability proof is used to show that, under the proposed adaptive control law, the paths converge to locally optimal configurations according to a Voronoi-based coverage task, i.e. informative paths. The problem is first treated for a single robot and then extended to multiple robots. Additionally, the controllers for both the single-robot and the multi-robot case are extended to treat the problem of generating informative paths for persistent sensing tasks. Persistent sensing tasks are concerned with controlling the trajectories of mobile robots to act in a growing field in the environment in a way that guarantees that the field remains bounded for all time. The extended informative path controllers are proven to shape the paths into informative paths that are useful for performing persistent sensing tasks. Lastly, prior work in persistent sensing tasks only considered robotic systems with collision-free paths. In this thesis we also describe a solution to multi-robot persistent sensing, where robots have intersecting trajectories. We develop collision and deadlock avoidance algorithms and quantify the impact of avoiding collision on the overall stability of the persistent sensing task. Simulated and experimental results support the proposed approach.by Daniel Eduardo Soltero.S.M

Collision avoidance for persistent monitoring in multi-robot systems with intersecting trajectories

Persistent robot tasks such as monitoring and cleaning are concerned with controlling mobile robots to act in a changing environment in a way that guarantees that the uncertainty in the system (due to change and to the actions of the robot) remains bounded for all time. Prior work in persistent robot tasks considered only robot systems with collision-free paths that move following speed controllers. In this paper we describe a solution to multi-robot persistent monitoring, where robots have intersecting trajectories. We develop collision and deadlock avoidance algorithms that are based on stopping policies, and quantify the impact of the stopping times on the overall stability of the speed controllers.United States. Office of Naval Research. Multidisciplinary University Research Initiative (Award N00014-09-1-1051)National Science Foundation (U.S.). Graduate Research Fellowship Program (Award 0645960)Boeing Compan

Annotating and quantifying pri-miRNA transcripts using RNA-Seq data of wild type and serrate-1 globular stage embryos of Arabidopsis thaliana

The genome annotation for the model plant Arabidopsis thaliana does not include the primary transcripts from which MIRNAs are processed. Here we present and analyze the raw mRNA sequencing data from wild type and serrate-1 globular stage embryos of A. thaliana, ecotype Columbia. Because SERRATE is required for pri-miRNA processing, these precursors accumulate in serrate-1 mutants, facilitating their detection using standard RNA-Seq protocols. We first use the mapping of the RNA-Seq reads to the reference genome to annotate the potential primary transcripts of MIRNAs expressed in the embryo. We then quantify these pri-miRNAs in wild type and serrate-1 mutants. Finally, we use differential expression analysis to determine which are up-regulated in serrate-1 compared to wild type, to select the best candidates of being bona fide pri-miRNAs expressed in the globular stage embryos. In addition, we analyze a previously published RNA-Seq dataset of wild type and dicer-like 1 mutant embryos at the globular stage. Our data are interpreted and discussed in a separate article.Peer reviewed: YesNRC publication: Ye

Genomic and ecological evidence shed light on the recent demographic history of two related invasive insects

Hypogeococcus pungens is a species complex native to southern South America that is composed of at least five putative species, each one specialized in the use of different host plants. Two of these undescribed species were registered as invasive in Central and North America: Hyp-C is a cactophagous mealybug that became an important pest that threatens endemic cactus species in Puerto Rico, and Hyp-AP feeds on Amaranthaceae and Portulacaceae hosts, but does not produce severe damage to the host plants. We quantified genomic variation and investigated the demographic history of both invasive species by means of coalescent-based simulations using high throughput sequencing data. We also evaluated the incidence of host plant infestation produced by both species and used an ecological niche modeling approach to assess potential distribution under current and future climatic scenarios. Our genetic survey evinced the footprints of strong effective population size reduction and signals of genetic differentiation among populations within each species. Incidence of plant attacks varied between species and among populations within species, with some host plant species preferred over others. Ecological niche modeling suggested that under future climatic scenarios both species would expand their distribution ranges in Puerto Rico. These results provide valuable information for the design of efficient management and control strategies of the Puerto Rican cactus pest and shed light on the evolutionary pathways of biological invasions.Fil: Poveda Martínez, Daniel Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Salinas, Nicolas Alejandro. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sánchez Restrepo, Andrés Fernando. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hight, Stephen. United States Department of Agriculture; Estados UnidosFil: Díaz-Soltero, Hilda. United States Department of Agriculture; Estados UnidosFil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Hasson, Esteban Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentin

Untangling the Hypogeococcus pungens species complex (Hemiptera: Pseudococcidae) for Argentina, Australia, and Puerto Rico based on host plant associations and genetic evidence

Hypogeococcus pungens, a mealybug native of southern South America, is devastating native cacti in Puerto Rico and threatening cactus diversity in the Caribbean, and potentially in Central and North America. The taxonomic status of H. pungens is controversial since it has been reported feeding not only on Cactaceae but also on other plant families throughout its distribution range. However, in Australia, where the species had been exported from Argentina to control weedy American cacti, it was never found on host plants other than Cactaceae. These conflicting pieces of evidence not only cast doubt on the species identity that invaded Puerto Rico, but also have a negative impact on the search for natural enemies to be used in biological control programs against this pest. Here we present reproductive incompatibility and phylogenetic evidences that give support to the hypothesis that H. pungens is a species complex in which divergence appears to be driven by the host plants. The nuclear EF1a and 18S and the mitochondrial COI genes were used as markers to evaluate the phylogenetic relationships among H. pungens populations collected in Argentina, Australia and Puerto Rico feeding on Cactaceae and/or Amaranthaceae. Additionally, we conducted reciprocal crosses between mealybugs from both hosts. Species delimitation analysis revealed two well-supported putative species within H. pungens, one including mealybugs feeding on Amaranthaceae (H. pungens sensu stricto), and a new undescribed species using Cactaceae as hosts. Additionally, we found asymmetric reproductive incompatibility between these putative species suggesting recent reproductive isolation. The Bayesian species delimitation also suggested that the Australian mealybug population may PLOS ONE derive from another undescribed species. Overall, the patterns of genetic differentiation may be interpreted as the result of recent speciation events prompted by host plant shifts. Finally, the finding of a single haplotype in the Puerto Rico population suggests only one invasive event. We still need to identify the geographical origin of the pest in order to enable the use of biological control to reduce the threat to cacti diversity in the Caribbean.Fil: Poveda Martínez, Daniel Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina. Universidad del Quindío; Colombia. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Calderón, Pablo Luciano Sebastian. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: de la Colina, María Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Hight, Stephen. United States Department of Agriculture; Estados UnidosFil: Triapitsyn, Serguei V.. University of California; Estados UnidosFil: Diaz Soltero, Hilda. United States Department of Agriculture; Estados UnidosFil: Hasson, Esteban Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentin

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.Swiss National Science Foundation (contract number PBEL2118737)United States. Army Research Office. Multidisciplinary University Research Initiative (MURI SWARMS project W911NF-05-1-0219)National Science Foundation (U.S.) (NSF IIS-0426838)Intel Corporation (EFRI 0735953 Intel)Massachusetts Institute of Technology (UROP program)Massachusetts Institute of Technology (MSRP program

Red Victoria

1 .pdf (1 Pag.) con texto descriptivo y 1 Fig. This EEAD-CSIC database – Variedades frutales de hueso y pepita is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.Manzano, Variedades frutales, Recursos genéticos, Malus domestica, Apple, Cultivars, Genetic Resources[EN] Pomological characterization, maturation time and fruit figure of apple cultivar described in “Cartografía de frutales de hueso y pepita” (Herrero J et al., 196

Decentralized path planning for coverage tasks using gradient descent adaptive control

In this paper we propose a new path planning algorithm for coverage tasks in unknown environments that does not rely on recursive search optimization. Given a sensory function that captures the interesting locations in the environment and can be learned, the goal is to compute a set of closed paths that allows a single robot or a multi-robot system to sense/cover the environment according to this function. We present an online adaptive distributed controller, based on gradient descent of a Voronoi-based cost function, that generates these closed paths, which the robots can travel for any coverage task, such as environmental mapping or surveillance. The controller uses local information only, and drives the robots to simultaneously identify the regions of interest and shape their paths online to sense these regions. Lyapunov theory is used to show asymptotic convergence of the system based on a Voronoi-based coverage criterion. Simulated and experimental results, that support the proposed approach, are presented for the single-robot and multi-robot cases in known and unknown environments. © The Author(s) 2013

Generating Informative Paths for Persistent Sensing in Unknown Environments

Abstract — We present an online algorithm for a robot to shape its path to a locally optimal configuration for collecting information in an unknown dynamic environment. As the robot travels along its path, it identifies both where the environment is changing, and how fast it is changing. The algorithm then morphs the robot’s path online to concentrate on the dynamic areas in the environment in proportion to their rate of change. A Lyapunov-like stability proof is used to show that, under our proposed path shaping algorithm, the path converges to a locally optimal configuration according to a Voronoi-based coverage criterion. The path shaping algorithm is then combined with a previously introduced speed controller to produce guaranteed persistent monitoring trajectories for a robot in an unknown dynamic environment. Simulation and experimental results with a quadrotor robot support the proposed approach. I