Vision-only autonomous navigation using topometric maps

This paper presents a mapping and navigation system for a mobile robot, which uses vision as its sole sensor modality. The system enables the robot to navigate autonomously, plan paths and avoid obstacles using a vision based topometric map of its environment. The map consists of a globally-consistent pose-graph with a local 3D point cloud attached to each of its nodes. These point clouds are used for direction independent loop closure and to dynamically generate 2D metric maps for locally optimal path planning. Using this locally semi-continuous metric space, the robot performs shortest path planning instead of following the nodes of the graph --- as is done with most other vision-only navigation approaches. The system exploits the local accuracy of visual odometry in creating local metric maps, and uses pose graph SLAM, visual appearance-based place recognition and point clouds registration to create the topometric map. The ability of the framework to sustain vision-only navigation is validated experimentally, and the system is provided as open-source software.

Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise

There has been considerable recent work on the development of energy conserving one-step methods that are not symplectic. Here we extend these ideas to stochastic Hamiltonian problems with additive noise and show that there are classes of Runge-Kutta methods that are very effective in preserving the expectation of the Hamiltonian, but care has to be taken in how the Wiener increments are sampled at each timestep. Some numerical simulations illustrate the performance of these methods.

Augmenting traversability maps with ultra-wideband radar to enhance obstacle detection in vegetated environments

Operating in vegetated environments is a major challenge for autonomous robots. Obstacle detection based only on geometric features causes the robot to consider foliage, for example, small grass tussocks that could be easily driven through, as obstacles. Classifying vegetation does not solve this problem since there might be an obstacle hidden behind the vegetation. In addition, dense vegetation typically needs to be considered as an obstacle. This paper addresses this problem by augmenting probabilistic traversability map constructed from laser data with ultra-wideband radar measurements. An adaptive detection threshold and a probabilistic sensor model are developed to convert the radar data to occupancy probabilities. The resulting map captures the fine resolution of the laser map but clears areas from the traversability map that are induced by obstacle-free foliage. Experimental results validate that this method is able to improve the accuracy of traversability maps in vegetated environments.

Reconstruction of the ancestral marsupial karyotype from comparative gene maps

BACKGROUND: The increasing number of assembled mammalian genomes makes it possible to compare genome organisation across mammalian lineages and reconstruct chromosomes of the ancestral marsupial and therian (marsupial and eutherian) mammals. However, the reconstruction of ancestral genomes requires genome assemblies to be anchored to chromosomes. The recently sequenced tammar wallaby (Macropus eugenii) genome was assembled into over 300,000 contigs. We previously devised an efficient strategy for mapping large evolutionarily conserved blocks in non-model mammals, and applied this to determine the arrangement of conserved blocks on all wallaby chromosomes, thereby permitting comparative maps to be constructed and resolve the long debated issue between a 2n=14 and 2n=22 ancestral marsupial karyotype. RESULTS: We identified large blocks of genes conserved between human and opossum, and mapped genes corresponding to the ends of these blocks by fluorescence in situ hybridization (FISH). A total of 242 genes was assigned to wallaby chromosomes in the present study, bringing the total number of genes mapped to 554 and making it the most densely cytogenetically mapped marsupial genome. We used these gene assignments to construct comparative maps between wallaby and opossum, which uncovered many intrachromosomal rearrangements, particularly for genes found on wallaby chromosomes X and 3. Expanding comparisons to include chicken and human permitted the putative ancestral marsupial (2n=14) and therian mammal (2n=19) karyotypes to be reconstructed. CONCLUSIONS: Our physical mapping data for the tammar wallaby has uncovered the events shaping marsupial genomes and enabled us to predict the ancestral marsupial karyotype, supporting a 2n=14 ancestor. Futhermore, our predicted therian ancestral karyotype has helped to understand the evolution of the ancestral eutherian genome.

Threshold privacy preserving keyword searches

We consider the following problem: users of an organization wish to outsource the storage of sensitive data to a large database server. It is assumed that the server storing the data is untrusted so the data stored have to be encrypted. We further suppose that the manager of the organization has the right to access all data, but a member of the organization can not access any data alone. The member must collaborate with other members to search for the desired data. In this paper, we investigate the notion of threshold privacy preserving keyword search (TPPKS) and define its security requirements. We construct a TPPKS scheme and show the proof of security under the assumptions of intractability of discrete logarithm, decisional Diffie-Hellman and computational Diffie-Hellman problems.

Linkage maps in pea

We have analyzed segregation patterns of markers among the late generation progeny of several crosses of pea. From the patterns of association of these markers we have deduced linkage orders. Salient features of these linkages are discussed, as is the relationship between the data presented here and previously published genetic and cytogenetic data.

Shared generation of pseudo-random functions with cumulative maps

In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

Lose yourself in books no more - interactive maps show the way

This article explores the use of digital technology such as interactive maps to enhance books.

Heat maps for aggregating bioacoustic annotations

In our large library of annotated environmental recordings of animal vocalizations, searching annotations by label can return thousands of results. We propose a heat map of aggregated annotation time and frequency bounds, maintaining the shape of the annotations as they appear on the spectrogram. This compactly displays the distribution of annotation bounds for the user's query, and allows them to easily identify unusual annotations. Key to this is allowing zero values on the map to be differentiated from areas where there are single annotations.

Functional brain maps of Tower of London performance : a positron emission tomography and functional magnetic resonance imaging study

Regional cerebral blood flow (rCBF) and blood oxygenation level-dependent (BOLD) contrasts represent different physiological measures of brain activation. The present study aimed to compare two functional brain imaging techniques (functional magnetic resonance imaging versus [15O] positron emission tomography) when using Tower of London (TOL) problems as the activation task. A categorical analysis (task versus baseline) revealed a significant BOLD increase bilaterally for the dorsolateral prefrontal and inferior parietal cortex and for the cerebellum. A parametric haemodynamic response model (or regression analysis) confirmed a task-difficulty-dependent increase of BOLD and rCBF for the cerebellum and the left dorsolateral prefrontal cortex. In line with previous studies, a task-difficulty-dependent increase of left-hemispheric rCBF was also detected for the premotor cortex, cingulate, precuneus, and globus pallidus. These results imply consistency across the two neuroimaging modalities, particularly for the assessment of prefrontal brain function when using a parametric TOL adaptation.

Non-market use and non-use values for preserving ecosystem services over time : a choice experiment application to coral reef ecosystems in New Caledonia

Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.

Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Genetics of path lengths in brain connectivity networks: HARDI-based maps in 457 adults

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.

Constructing abstract maps from spatial descriptions for goal-directed exploration

This paper describes ongoing work on a system using spatial descriptions to construct abstract maps that can be used for goal-directed exploration in an unfamiliar office environment. Abstract maps contain membership, connectivity, and spatial layout information extracted from symbolic spatial information. In goal-directed exploration, the robot would then link this information with observed symbolic information and its grounded world representation. We demonstrate the ability of the system to extract and represent membership, connectivity, and spatial layout information from spatial descriptions of an office environment. In the planned study, the robot will navigate to the goal location using the abstract map to inform the best direction to explore in.