pinecone/core-2020-05-10-deduplication huggingface dataset:
Air-ground matching: appearance-based GPS-denied urban localization of micro aerial vehicles

In this paper, we address the problem of globally localizing and tracking the pose of a camera-equipped micro aerial vehicle (MAV) flying in urban streets at low altitudes without GPS. An image-based global positioning system is introduced to localize the MAV with respect to the surrounding buildings. We propose a novel air-ground image-matching algorithm to search the airborne image of the MAV within a ground-level, geotagged image database. Based on the detected matching image features, we infer the global position of the MAV by back-projecting the corresponding image points onto a cadastral three-dimensional city model. Furthermore, we describe an algorithm to track the position of the flying vehicle over several frames and to correct the accumulated drift of the visual odometry whenever a good match is detected between the airborne and the ground-level images. The proposed approach is tested on a 2 km trajectory with a small quadrocopter flying in the streets of Zurich. Our vision-based global localization can robustly handle extreme changes in viewpoint, illumination, perceptual aliasing, and over-season variations, thus outperforming conventional visual place-recognition approaches. The dataset is made publicly available to the research community. To the best of our knowledge, this is the first work that studies and demonstrates global localization and position tracking of a drone in urban streets with a single onboard camera
3D Scan Registration using Curvelet Features in Planetary Environments

Topographic mapping in planetary environments relies on accurate 3D scan
registration methods. However, most global registration algorithms relying on
features such as FPFH and Harris-3D show poor alignment accuracy in these
settings due to the poor structure of the Mars-like terrain and variable
resolution, occluded, sparse range data that is hard to register without some
a-priori knowledge of the environment. In this paper, we propose an alternative
approach to 3D scan registration using the curvelet transform that performs
multi-resolution geometric analysis to obtain a set of coefficients indexed by
scale (coarsest to finest), angle and spatial position. Features are detected
in the curvelet domain to take advantage of the directional selectivity of the
transform. A descriptor is computed for each feature by calculating the 3D
spatial histogram of the image gradients, and nearest neighbor based matching
is used to calculate the feature correspondences. Correspondence rejection
using Random Sample Consensus identifies inliers, and a locally optimal
Singular Value Decomposition-based estimation of the rigid-body transformation
aligns the laser scans given the re-projected correspondences in the metric
space. Experimental results on a publicly available data-set of planetary
analogue indoor facility, as well as simulated and real-world scans from Neptec
Design Group's IVIGMS 3D laser rangefinder at the outdoor CSA Mars yard
demonstrates improved performance over existing methods in the challenging
sparse Mars-like terrain.Comment: 27 pages in Journal of Field Robotics, 201
An automated emergency landing system for fixed-wing aircraft: Planning and control

A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure and aircraft. To date, few field-demonstrated systems have been presented that show online re-planning and repeatability from failure to touchdown. This paper presents the development of the Guidance, Navigation and Control (GNC) component of an Automated Emergency Landing System (AELS) intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories and a simplified control system executes the required manoeuvres to guide the aircraft towards touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and re-plans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases
Trafficability Assessment of Deformable Terrain through Hybrid Wheel-Leg Sinkage Detection

Off-road ground mobile robots are widely used in diverse applications, both in terrestrial and planetary environments. They provide an efficient alternative, with lower risk and cost, to explore or to transport materials through hazardous or challenging terrain. However, nongeometric hazards that cannot be detected remotely pose a serious threat to the mobility of such robots. A prominent example of the negative effects these hazards can have is found on planetary rover exploration missions. They can cause a serious degradation of mission performance at best and complete immobilization and mission failure at worst. To tackle this issue, the work presented in this paper investigates the novel application of an existing enhanced-mobility locomotion concept, a hybrid wheel-leg equipped by a lightweight micro-rover, for in situ characterization of deformable terrain and online detection of nongeometric hazards. This is achieved by combining an improved vision-based approach and a new ranging-based approach to wheel-leg sinkage detection. In addition, the paper proposes an empirical model, and a parametric generalization, to predict terrain trafficability based on wheel-leg sinkage and a well-established semiempirical terramechanics model. The robustness and accuracy of the sinkage detection methods implemented are tested in a variety of conditions, both in the laboratory and in the field, using a single wheel-leg test bed. The sinkage-trafficability model is developed based on experimental data using this test bed and then validated onboard a fully mobile robot through experimentation on a range of dry frictional soils that covers a wide spectrum of macroscopic physical characteristics
Nonparametric traversability estimation in partially occluded and deformable terrain

Terrain traversability estimation is a fundamental requirement to ensure the safety of autonomous planetary rovers and their ability to conduct long-term missions. This paper addresses two fundamental challenges for terrain traversability estimation techniques. First, representations of terrain data, which are typically built by the rover’s onboard exteroceptive sensors, are often incomplete due to occlusions and sensor limitations. Second, during terrain traversal, the rover-terrain interaction can cause terrain deformation, which may significantly alter the difficulty of traversal. We propose a novel approach built on Gaussian process (GP) regression to learn, and consequently to predict, the rover’s attitude and chassis configuration on unstructured terrain using terrain geometry information only. First, given incomplete terrain data, we make an initial prediction under the assumption that the terrain is rigid, using a learnt kernel function. Then, we refine this initial estimate to account for the effects of potential terrain deformation, using a near-to-far learning approach based on multitask GP regression. We present an extensive experimental validation of the proposed approach on terrain that is mostly rocky and whose geometry changes as a result of loads from rover traversals. This demonstrates the ability of the proposed approach to accurately predict the rover’s attitude and configuration in partially occluded and deformable terrain
Vertical Landing for Micro Air Vehicles using Event-Based Optical Flow

Small flying robots can perform landing maneuvers using bio-inspired optical
flow by maintaining a constant divergence. However, optical flow is typically
estimated from frame sequences recorded by standard miniature cameras. This
requires processing full images on-board, limiting the update rate of
divergence measurements, and thus the speed of the control loop and the robot.
Event-based cameras overcome these limitations by only measuring pixel-level
brightness changes at microsecond temporal accuracy, hence providing an
efficient mechanism for optical flow estimation. This paper presents, to the
best of our knowledge, the first work integrating event-based optical flow
estimation into the control loop of a flying robot. We extend an existing
'local plane fitting' algorithm to obtain an improved and more computationally
efficient optical flow estimation method, valid for a wide range of optical
flow velocities. This method is validated for real event sequences. In
addition, a method for estimating the divergence from event-based optical flow
is introduced, which accounts for the aperture problem. The developed
algorithms are implemented in a constant divergence landing controller on-board
of a quadrotor. Experiments show that, using event-based optical flow, accurate
divergence estimates can be obtained over a wide range of speeds. This enables
the quadrotor to perform very fast landing maneuvers.Comment: 29 pages, 14 figures, under peer revie
Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

One of the most challenging tasks for a flying robot is to autonomously
navigate between target locations quickly and reliably while avoiding obstacles
in its path, and with little to no a-priori knowledge of the operating
environment. This challenge is addressed in the present paper. We describe the
system design and software architecture of our proposed solution, and showcase
how all the distinct components can be integrated to enable smooth robot
operation. We provide critical insight on hardware and software component
selection and development, and present results from extensive experimental
testing in real-world warehouse environments. Experimental testing reveals that
our proposed solution can deliver fast and robust aerial robot autonomous
navigation in cluttered, GPS-denied environments.Comment: Pre-peer reviewed version of the article accepted in Journal of Field
  Robotic
Design, Control and Visual Navigation of the DelftaCopter

To participate in the Outback Medical Express UAV Challenge 2016, a vehicle
was designed and tested that can hover precisely, take-off and land vertically,
fly fast forward efficiently and use computer vision to locate a person and a
suitable landing location. A rotor blade was designed that can deliver
sufficient thrust in hover, while still being efficient in fast forward flight.
Energy measurements and windtunnel tests were performed. A rotor-head and
corresponding control algorithms were developed to allow transitioning flight
with the non-conventional rotor dynamics. Dedicated electronics were designed
that meet vehicle needs and regulations to allow safe flight beyond visual line
of sight. Vision based search and guidance algorithms were developed and
tested. Flight tests and a competition participation illustrate the
applicability of the DelftaCopter concept
TrackerBots: Autonomous UAV for Real-Time Localization and Tracking of
  Multiple Radio-Tagged Animals

Autonomous aerial robots provide new possibilities to study the habitats and
behaviors of endangered species through the efficient gathering of location
information at temporal and spatial granularities not possible with traditional
manual survey methods. We present a novel autonomous aerial vehicle
system-TrackerBots-to track and localize multiple radio-tagged animals. The
simplicity of measuring the received signal strength indicator (RSSI) values of
very high frequency (VHF) radio-collars commonly used in the field is exploited
to realize a low cost and lightweight tracking platform suitable for
integration with unmanned aerial vehicles (UAVs). Due to uncertainty and the
nonlinearity of the system based on RSSI measurements, our tracking and
planning approaches integrate a particle filter for tracking and localizing; a
partially observable Markov decision process (POMDP) for dynamic path planning.
This approach allows autonomous navigation of a UAV in a direction of maximum
information gain to locate multiple mobile animals and reduce exploration time;
and, consequently, conserve onboard battery power. We also employ the concept
of a search termination criteria to maximize the number of located animals
within power constraints of the aerial system. We validated our real-time and
online approach through both extensive simulations and field experiments with
two mobile VHF radio-tags.Comment: Submitted to the Journal of Field Robotic
Estimation model for kinematic calibration of manipulators with a parallel structure

This article provides an estimation model for calibrating the kinematics of manipulators with a parallel geometrical structure. Parameter estimation for serial link manipulators is well developed, but fail for most structures with parallel actuators, because the forward kinematics is usually not analytically available for these. We extend parameter estimation to such parallel structures by developing an estimation method where errors in kinematical parameters are linearly related to errors in the tool pose, expressed through the inverse kinematics, which is usually well known. The method is based on the work done to calibrate the MultiCraft robot. This robot has five linear actuators built in parallel around a passive serial arm, thus making up a two-layered parallel-serial manipulator, and the unique MultiCraft construction is reviewed. Due to the passive serial arm, for this robot conventional serial calibration must be combined with estimation of the parameters in the parallel actuator structure. The developed kinematic calibration method is verified through simulations with realistic data and real robot kinematics, taking the MultiCraft manipulator as the case
Enhanced chemical weathering as a geoengineering strategy to reduce atmospheric carbon dioxide, supply nutrients, and mitigate ocean acidification

Chemical weathering is an integral part of both the rock and carbon cycles and is being affected by changes in land use, particularly as a result of agricultural practices such as tilling, mineral fertilization, or liming to adjust soil pH. These human activities have already altered the chemical terrestrial cycles and land-ocean flux of major elements, although the extent remains difficult to quantify. When deployed on a grand scale, Enhanced Weathering (a form of mineral fertilization), the application of finely ground minerals over the land surface, could be used to remove CO2 from the atmosphere. The release of cations during the dissolution of such silicate minerals would convert dissolved CO2 to bicarbonate, increasing the alkalinity and pH of natural waters. Some products of mineral dissolution would precipitate in soils or taken up by ecosystems, but a significant portion would be transported to the coastal zone and the open ocean, where the increase in alkalinity would partially counteract “ocean acidification” associated with the current marked increase in atmospheric CO2. Other elements released during this mineral dissolution, like Si, P or K, could stimulate biological productivity, further helping to remove CO2 from the atmosphere. On land, the terrestrial carbon-pool would likely increase in response to Enhanced Weathering in areas where ecosystem growth rates are currently limited by one of the nutrients that would be released during mineral dissolution. In the ocean, the biological carbon pumps (which export organic matter and CaCO3 to the deep ocean) may be altered by the resulting influx of nutrients and alkalinity to the ocean. This review merges current interdisciplinary knowledge about Enhanced Weathering, the processes involved, and the applicability as well as some of the consequences and risks of applying the method
Modeling the interactions between river morphodynamics and riparian vegetation

The study of river-riparian vegetation interactions is an important and intriguing research field in geophysics. Vegetation is an active element of the ecological dynamics of a floodplain which interacts with the fluvial processes and affects the flow field, sediment transport, and the morphology of the river. In turn, the river provides water, sediments, nutrients, and seeds to the nearby riparian vegetation, depending on the hydrological, hydraulic, and geomorphological characteristic of the stream. In the past, the study of this complex theme was approached in two different ways. On the one hand, the subject was faced from a mainly qualitative point of view by ecologists and biogeographers. Riparian vegetation dynamics and its spatial patterns have been described and demonstrated in detail, and the key role of several fluvial processes has been shown, but no mathematical models have been proposed. On the other hand, the quantitative approach to fluvial processes, which is typical of engineers, has led to the development of several morphodynamic models. However, the biological aspect has usually been neglected, and vegetation has only been considered as a static element. In recent years, different scientific communities (ranging from ecologists to biogeographers and from geomorphologists to hydrologists and fluvial engineers) have begun to collaborate and have proposed both semiquantitative and quantitative models of river-vegetation interconnections. These models demonstrate the importance of linking fluvial morphodynamics and riparian vegetation dynamics to understand the key processes that regulate a riparian environment in order to foresee the impact of anthropogenic actions and to carefully manage and rehabilitate riparian areas. In the first part of this work, we review the main interactions between rivers and riparian vegetation, and their possible modeling. In the second part, we discuss the semiquantitative and quantitative models which have been proposed to date, considering both multi- and single-thread river
A review of climatic controls on delta 18O in precipitation over the Tibetan Plateau: Observations and simulations

The stable oxygen isotope ratio (δ18O) in precipitation is an integrated tracer of atmospheric processes worldwide. Since the 1990s, an intensive effort has been dedicated to studying precipitation isotopic composition at more than 20 stations in the Tibetan Plateau (TP) located at the convergence of air masses between the westerlies and Indian monsoon. In this paper, we establish a database of precipitation δ18O and use different models to evaluate the climatic controls of precipitation δ18O over the TP. The spatial and temporal patterns of precipitation δ18O and their relationships with temperature and precipitation reveal three distinct domains, respectively associated with the influence of the westerlies (northern TP), Indian monsoon (southern TP), and transition in between. Precipitation δ18O in the monsoon domain experiences an abrupt decrease in May and most depletion in August, attributable to the shifting moisture origin between Bay of Bengal (BOB) and southern Indian Ocean. High-resolution atmospheric models capture the spatial and temporal patterns of precipitation δ18O and their relationships with moisture transport from the westerlies and Indian monsoon. Only in the westerlies domain are atmospheric models able to represent the relationships between climate and precipitation δ18O. More significant temperature effect exists when either the westerlies or Indian monsoon is the sole dominant atmospheric process. The observed and simulated altitude-δ18O relationships strongly depend on the season and the domain (Indian monsoon or westerlies). Our results have crucial implications for the interpretation of paleoclimate records and for the application of atmospheric simulations to quantifying paleoclimate and paleo-elevation changes
Macroinvertebrate community response to inter-annual and regional river flow regime dynamics

This article was submitted for publication in the journal, River Research and Applications [© 2008 John Wiley & Sons, Ltd.] and the definitive version is available at: http://dx.doi.org/10.1002/rra.1120Spatio-temporal variability in river flow is a fundamental control on instream habitat structure and riverine ecosystem biodiversity and integrity. However, long-term riverine ecological time-series to test hypotheses about hydrology–ecology interactions in a broader temporal context are rare, and studies spanning multiple rivers are often limited in their temporal coverage to less than five years. To address this research gap, a unique spatio-temporal hydroecological analysis was conducted of long-term instream ecological responses (1990–2000) to river flow regime variability at 83 sites across England and Wales. The results demonstrate clear hydroecological associations at the national scale (all data). In addition, significant differences in ecological response are recorded between three ‘regions’ identified (RM1–3*) associated with characteristics of the flow regime. The effect of two major supra-seasonal droughts (1990–1992 and 1996–1997) on inter-annual (IA) variability of the LIFE scores is evident with both events showing a gradual decline before and recovery of LIFE scores after the low flow period. The instream community response to high magnitude flow regimes (1994 and 1995) is also apparent, although these associations are less striking. The results demonstrate classification of rivers into flow regime regions offers a way to help unravel complex hydroecological associations. The approach adopted herein could easily be adapted for other geographical locations, where datasets are available. Such work is imperative to understand flow regime–ecology interactions in a longer term, wider spatial context and so assess future hydroecological responses to climate change and anthropogenic modification of riverine ecosystems