Mobile robot control on uneven and slippery ground: An adaptive approach based on a multi-model observer

International audienceThis paper proposes an algorithm dedicated to off-road mobile robot path tracking at high speed. In order to ensure a high accuracy, a predictive and adaptive approach is developed to face the various perturbations due to this context (mainly the bad grip conditions and the terrain geometry). The control law is based on previous work, and requires the knowledge of sideslip angles, which cannot be directly measured. As a result, an observer based on two levels of modeling (kinematic and dynamic) is proposed to ensure a relevant and fast estimation. If the kinematic part is independent from the terrain geometry, the dynamic model used in this paper requires to take explicitly into account the influence of the terrain geometry on mobile robot dynamic. It is achieved by the introduction of the lateral robot inclination, which is on-line estimated via a kalman filter and integrated in the dynamical model. The advantages of the proposed contribution to path tracking control are investigated through full-scale experiments achieved at high speed (up to 6m/s) on an uneven and grass field

The Star Formation History of the Large Magellanic Cloud

We present the first-ever global, spatially-resolved reconstruction of the star formation history (SFH) of the Large Magellanic Cloud (LMC), based on the application of our StarFISH analysis software to the multiband photometry of twenty million of its stars from the Magellanic Clouds Photometric Survey. The general outlines of our results are consistent with previously published results: following an initial burst of star formation, there was a quiescent epoch from approximately 12 to 5 Gyr ago. Star formation then resumed and has proceeded until the current time at an average rate of roughly 0.2 solar masses/yr, with temporal variations at the factor-of-two level. The re-ignition of star formation about 5 Gyr ago, in both the LMC and SMC, is suggestive of a dramatic event at that time in the Magellanic system. Among the global variations in the recent star formation rate are peaks at roughly 2 Gyr, 500 Myr, 100 Myr and 12 Myr. The peaks at 500 Myr and 2 Gyr are nearly coincident with similar peaks in the SFH of the Small Magellanic Cloud, suggesting a joint history for these galaxies extending back at least several Gyr. The chemical enrichment history recovered from our StarFISH analysis is in broad agreement with that inferred from the LMC's star cluster population, although our constraints on the ancient chemical enrichment history are weak. We conclude from the concordance between the star formation and chemical enrichment histories of the field and cluster populations that the field and cluster star formation modes are tightly coupled.Comment: 20 pages, with color figures. Accepted for publication in A

Digital elevation modelling by radargrammetry in real-beam ground mapping mode

In this thesis the problem of estimating terrain elevation using two-dimensional radar data from the multirole ghter aircraft JAS 39 Gripen is considered. Radar data contains information about range from the aircraft to the reflecting terrain, as well as horizontal angle. In general, radar data has high resolution in range and low resolution in angle, giving rise to interesting problems. A new radar with higher resolution is in development for the next-generation Gripen. This thesis aims at answering whether estimation of terrain height can be done using available radar data, in order to evaluate the plausibility of doing this with data from the new radar. The approach is to find matching terrain features in subsequent images of the ground, and use this information to calculate terrain elevation. Two approaches are implemented and studied, both on simulated radar data and on real datasets. One approach uses Harris corner detection and the other uses Speeded-Up Robust Features (SURF). Conclusions drawn are that the algorithms do not work for the available radar data, but that they possibly could work when higher resolution data from the new radar is available

Soil erosion in the Alps : causes and risk assessment

The issue of soil erosion in the Alps has long been neglected due to the low economic value of the agricultural land. However, soil stability is a key parameter which affects ecosystem services like slope stability, water budgets (drinking water reservoirs as well as flood prevention), vegetation productivity, ecosystem biodiversity and nutrient production. In alpine regions, spatial estimates on soil erosion are difficult to derive because the highly heterogeneous biogeophysical structure impedes measurement of soil erosion and the applicability of soil erosion models. However, remote sensing and geographic information system (GIS) methods allow for spatial estimation of soil erosion by direct detection of erosion features and supply of input data for soil erosion models. Thus, the main objective of this work is to address the problem of soil erosion risk assessment in the Alps on catchment scale with remote sensing and GIS tools. Regarding soil erosion processes the focus is on soil erosion by water (here sheet erosion) and gravity (here landslides). For these two processes we address i) the monitoring and mapping of the erosion features and related causal factors ii) soil erosion risk assessment with special emphasis on iii) the validation of existing models for alpine areas. All investigations were accomplished in the Urseren Valley (Central Swiss Alps) where the valley slopes are dramatically affected by sheet erosion and landslides. For landslides, a natural susceptibility of the catchment has been indicated by bivariate and multivariate statistical analysis. Geology, slope and stream density are the most significant static landslide causal factors. Static factors are here defined as factors that do not change their attributes during the considered time span of the study (45 years), e.g. geology, stream network. The occurrence of landslides might be significantly increased by the combined effects of global climate and land use change. Thus, our hypothesis is that more recent changes in land use and climate affected the spatial and temporal occurrence of landslides. The increase of the landslide area of 92% within 45 years in the study site confirmed our hypothesis. In order to identify the cause for the trend in landslide occurrence time-series of landslide causal factors were analysed. The analysis revealed increasing trends in the frequency and intensity of extreme rainfall events and stocking of pasture animals. These developments presumably enhanced landslide hazard. Moreover, changes in land-cover and land use were shown to have affected landslide occurrence. For instance, abandoned areas and areas with recently emerging shrub vegetation show very low landslide densities. Detailed spatial analysis of the land use with GIS and interviews with farmers confirmed the strong influence of the land use management practises on slope stability. The definite identification and quantification of the impact of these non-stationary landslide causal factors (dynamic factors) on the landslide trend was not possible due to the simultaneous change of several factors. The consideration of dynamic factors in statistical landslide susceptibility assessments is still unsolved. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. Thus, we evaluated the effect of dynamic landslide causal factors on the validity of landslide susceptibility maps for spatial and temporal predictions. For this purpose, a logistic regression model based on data of the year 2000 was set up. The resulting landslide susceptibility map was valid for spatial predictions. However, the model failed to predict the landslides that occurred in a subsequent event. In order to handle this weakness of statistic landslide modelling a multitemporal approach was developed. It is based on establishing logistic regression models for two points in time (here 1959 and 2000). Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of dynamic causal factors on the landslide probability. The deviation map explained 85% of new independent landslides occurring after 2000. Thus, we believe it to be a suitable tool to add a time element to a susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions or human interactions. In contrast to landslides that are a direct threat to buildings and infrastructure, sheet erosion attracts less attention because it is often an unseen process. Nonetheless, sheet erosion may account for a major proportion of soil loss. Soil loss by sheet erosion is related to high spatial variability, however, in contrast to arable fields for alpine grasslands erosion damages are long lasting and visible over longer time periods. A crucial erosion triggering parameter that can be derived from satellite imagery is fractional vegetation cover (FVC). Measurements of the radiogenic isotope Cs-137, which is a common tracer for soil erosion, confirm the importance of FVC for soil erosion yield in alpine areas. Linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and the spectral index NDVI are applied for estimating fractional abundance of vegetation and bare soil. To account for the small scale heterogeneity of the alpine landscape very high resolved multispectral QuickBird imagery is used. The performance of LSU and MTMF for estimating percent vegetation cover is good (r²=0.85, r²=0.71 respectively). A poorer performance is achieved for bare soil (r²=0.28, r²=0.39 respectively) because compared to vegetation, bare soil has a less characteristic spectral signature in the wavelength domain detected by the QuickBird sensor. Apart from monitoring erosion controlling factors, quantification of soil erosion by applying soil erosion risk models is done. The performance of the two established models Universal Soil Loss Equation (USLE) and Pan-European Soil Erosion Risk Assessment (PESERA) for their suitability to model erosion for mountain environments is tested. Cs-137 is used to verify the resulting erosion rates from USLE and PESERA. PESERA yields no correlation to measured Cs-137 long term erosion rates and shows lower sensitivity to FVC. Thus, USLE is used to model the entire study site. The LSU-derived FVC map is used to adapt the C factor of the USLE. Compared to the low erosion rates computed with the former available low resolution dataset (1:25000) the satellite supported USLE map shows “hotspots” of soil erosion of up to 16 t ha-1 a-1. In general, Cs-137 in combination with the USLE is a very suitable method to assess soil erosion for larger areas, as both give estimates on long-term soil erosion. Especially for inaccessible alpine areas, GIS and remote sensing proved to be powerful tools that can be used for repetitive measurements of erosion features and causal factors. In times of global change it is of crucial importance to account for temporal developments. However, the evaluation of the applied soil erosion risk models revealed that the implementation of temporal aspects, such as varying climate, land use and vegetation cover is still insufficient. Thus, the proposed validation strategies (spatial, temporal and via Cs-137) are essential. Further case studies in alpine regions are needed to test the methods elaborated for the Urseren Valley. However, the presented approaches are promising with respect to improve the monitoring and identification of soil erosion risk areas in alpine regions

The synthesis of estuarine bathymetry from sparse sounding data

The two aims of the project involved: 1. Devising a system for prediction o f areas of bathymetric change within the Fal estuary 2. Formulating and evaluating a method for interpolating single beam acoustic bathymetry to avoid artefacts o f interpolation. In order to address these aims, sources of bathymetric data for the Fal estuary were identified as Truro Harbour Office, Cornwall County Council and the Environment Agency. The data collected from these sources included red wavelength Lidar, aerial photography and single beam acoustic bathymetry from a number of different years. These data were input into a Geographic Information System (GIS) and assessed for suitability for the purposes o f data comparison and hence assessment of temporal trends in bathymetry within the estuary Problems encountered during mterpolation of the acoustic bathymetry resulted in the later aim of the project, to formulate an interpolation system suitable for interpolation of the single beam, bathymetric data in a realistic way, avoiding serious artefacts of interpolation. This aim was met, successfully, through the following processes: 1. An interpolation system was developed, using polygonal zones, bounded by channels and coastlines, to prevent interpolation across these boundaries. This system, based on Inverse Distance Weighting (IDW) interpolation, was referred to as Zoned Inverse Distance Weighting (ZIDW). 2. ZIDW was found, by visual inspection, to eliminate the interpolation artefacts described above. 3. The processes of identification of sounding lines and charmels, and the allocation of soundings and output grid cells to polygons, were successfully automated to allow ZIDW to be applied to large and multiple data sets. Manual intervention was maintained for processes performed most successfully by the human brain to optimise the results o f ZIDW. 4. To formalise the theory of ZIDW it was applied to a range of idealised, mathematically defined chaimels. For simple straight and regular curved, mathematical channels interpolation by the standard TIN method was found to perform as well as ZIDW. 5. Investigation of sinusoidal channels within a rectangular estuary, however, revealed that the TIN method begins to produce serious interpolation artefacts where sounding lines are not parallel to the centre lines o f channels and ridges. Hence, overall ZIDW was determined mathematically to represent the optimum method o f interpolation for single beam, bathymelric data. 6. Finally, ZIDW was refined, using data from the Humber and Gironde estuaries, to achieve universal applicability for interpolation of single beam, echo soimding data from any estuary. 7. The refinements involved allowance for non-continuous, flood and ebb type charmels; consideration of the effects of the scale of the estuary; smoothing of the channels using cubic splines; interpolation using a 'smart' ellipse and the option to reconstruct sounding lines from data that had previously been re-ordered

Semi-automated geomorphological mapping applied to landslide hazard analysis

Computer-assisted three-dimensional (3D) mapping using stereo and multi-image (“softcopy”) photogrammetry is shown to enhance the visual interpretation of geomorphology in steep terrain with the direct benefit of greater locational accuracy than traditional manual mapping. This would benefit multi-parameter correlations between terrain attributes and landslide distribution in both direct and indirect forms of landslide hazard assessment. Case studies involve synthetic models of a landslide, and field studies of a rock slope and steep undeveloped hillsides with both recently formed and partly degraded, old landslide scars. Diagnostic 3D morphology was generated semi-automatically both using a terrain-following cursor under stereo-viewing and from high resolution digital elevation models created using area-based image correlation, further processed with curvature algorithms. Laboratory-based studies quantify limitations of area-based image correlation for measurement of 3D points on planar surfaces with varying camera orientations. The accuracy of point measurement is shown to be non-linear with limiting conditions created by both narrow and wide camera angles and moderate obliquity of the target plane. Analysis of the results with the planar surface highlighted problems with the controlling parameters of the area-based image correlation process when used for generating DEMs from images obtained with a low-cost digital camera. Although the specific cause of the phase-wrapped image artefacts identified was not found, the procedure would form a suitable method for testing image correlation software, as these artefacts may not be obvious in DEMs of non-planar surfaces.Modelling of synthetic landslides shows that Fast Fourier Transforms are an efficient method for removing noise, as produced by errors in measurement of individual DEM points, enabling diagnostic morphological terrain elements to be extracted. Component landforms within landslides are complex entities and conversion of the automatically-defined morphology into geomorphology was only achieved with manual interpretation; however, this interpretation was facilitated by softcopy-driven stereo viewing of the morphological entities across the hillsides.In the final case study of a large landslide within a man-made slope, landslide displacements were measured using a photogrammetric model consisting of 79 images captured with a helicopter-borne, hand-held, small format digital camera. Displacement vectors and a thematic geomorphological map were superimposed over an animated, 3D photo-textured model to aid non-stereo visualisation and communication of results

A multi-dimensional stability model for predicting shallow landslide size and shape across landscapes

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory, and by representing root reinforcement as an exponential function of soil depth. We test our model’s ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data