Unmanned Aerial Vehicle (UAV) for monitoring soil erosion in Morocco

This article presents an environmental remote sensing application using a UAV that is specifically aimed at reducing the data gap between field scale and satellite scale in soil erosion monitoring in Morocco. A fixed-wing aircraft type Sirius I (MAVinci, Germany) equipped with a digital system camera (Panasonic) is employed. UAV surveys are conducted over different study sites with varying extents and flying heights in order to provide both very high resolution site-specific data and lower-resolution overviews, thus fully exploiting the large potential of the chosen UAV for multi-scale mapping purposes. Depending on the scale and area coverage, two different approaches for georeferencing are used, based on high-precision GCPs or the UAV’s log file with exterior orientation values respectively. The photogrammetric image processing enables the creation of Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimetre level. The created data products were used for quantifying gully and badland erosion in 2D and 3D as well as for the analysis of the surrounding areas and landscape development for larger extents

Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies

A fundamentally new (scientific) reconnaissance mission concept, termed tier-scalable reconnaissance, for remote planetary (including Earth) atmospheric, surface and subsurface exploration recently has been devised that soon will replace the engineering and safety constrained mission designs of the past, allowing for optimal acquisition of geologic, paleohydrologic, paleoclimatic, and possible astrobiologic information of Venus, Mars, Europa, Ganymede, Titan, Enceladus, Triton, and other extraterrestrial targets. This paradigm is equally applicable to potentially hazardous or inaccessible operational areas on Earth such as those related to military or terrorist activities, or areas that have been exposed to biochemical agents, radiation, or natural disasters. Traditional missions have performed local, ground-level reconnaissance through rovers and immobile landers, or global mapping performed by an orbiter. The former is safety and engineering constrained, affording limited detailed reconnaissance of a single site at the expense of a regional understanding, while the latter returns immense datasets, often overlooking detailed information of local and regional significance

The Performance Assessment of a Small Lighter-Than-Air Vehicle for Earth Science Remote Sensing Missions

This summer, a lighter-than-air (LTA) drone was tested in Alaska to measure glacier bedrock fracture density and orientation. Five flights were made in low wind conditions, and the directional stability of the airship made it too challenging to control in flight to realistically acquire useful image sets. The directional stability of the airship, when compared to an actively stabilized consumer-grade quadcopter was inferior. Flight logs and GPS data from the GPS on the LTA drone were analyzed and a quantitative assessment of the observed instability was made. The yaw axis and pitch were analyzed, and the yaw axis instability was greater than the pitch axis instability. The source of this instability included the excessive sensitivity of the yaw thruster, and the inherent yaw instability of the blimp shape. An attempt was made to reduce the yaw instability by reducing the yaw motor size. The observed instability may have also resulted from external sources like wind gusts and the glacier microclimate. The analysis informed modifications of the LTA drone to make it more stable for glacier research, which were implemented and tested. The thrust output of the tail motor was reduced by 59%. This change was associated with a reduction in median heading variability of 47% between test flights before and after modification. The reduction was proven statistically significant at a 99% confidence interval. Also, recommendations for further modifications include the implementation of autonomous flight control and envelope optimization

Automated Global Feature Analyzer - A Driver for Tier-Scalable Reconnaissance

For the purposes of space flight, reconnaissance field geologists have trained to become astronauts. However, the initial forays to Mars and other planetary bodies have been done by purely robotic craft. Therefore, training and equipping a robotic craft with the sensory and cognitive capabilities of a field geologist to form a science craft is a necessary prerequisite. Numerous steps are necessary in order for a science craft to be able to map, analyze, and characterize a geologic field site, as well as effectively formulate working hypotheses. We report on the continued development of the integrated software system AGFA: automated global feature analyzerreg, originated by Fink at Caltech and his collaborators in 2001. AGFA is an automatic and feature-driven target characterization system that operates in an imaged operational area, such as a geologic field site on a remote planetary surface. AGFA performs automated target identification and detection through segmentation, providing for feature extraction, classification, and prioritization within mapped or imaged operational areas at different length scales and resolutions, depending on the vantage point (e.g., spaceborne, airborne, or ground). AGFA extracts features such as target size, color, albedo, vesicularity, and angularity. Based on the extracted features, AGFA summarizes the mapped operational area numerically and flags targets of "interest", i.e., targets that exhibit sufficient anomaly within the feature space. AGFA enables automated science analysis aboard robotic spacecraft, and, embedded in tier-scalable reconnaissance mission architectures, is a driver of future intelligent and autonomous robotic planetary exploration

Tier-scalable reconnaissance: the challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

Robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit atmosphere surface/subsurface) and multi-agent (satellite UAV/blimp surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring); (2) automatic feature extraction and target/region-of-interest identification within the mapped operational area; and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability

Towards the Realization of an Autonomous Blimp

This project continues an MQP from the 2011-12 academic year: Development of an Autonomous Blimp. The objective of our project was to modify the existing design by implementing autonomous flight capability using an Android phone, a power system capable of tracking energy usage, and a camera mission module for aerial photography. Through testing and flight tests, we demonstrated that we successfully implemented non-optimized autonomous flight, portions of the power system design, and a camera mission module

Towards the Realization of an Autonomous Blimp

This project continues an MQP from the 2011-12 academic year: Development of an Autonomous Blimp. The objective of our project was to modify the existing design by implementing autonomous flight capability using an Android phone, a power system capable of tracking energy usage, and a camera mission module for aerial photography. Through testing and flight tests, we demonstrated that we successfully implemented non-optimized autonomous flight, portions of the power system design, and a camera mission module