Evaluation of laser range-finder mapping for agricultural spraying vehicles

In this paper, we present a new application of laser range-finder sensing to agricultural spraying vehicles. The current generation of spraying vehicles use automatic controllers to maintain the height of the sprayer booms above the crop. However, these control systems are typically based on ultrasonic sensors mounted on the booms, which limits the accuracy of the measurements and the response of the controller to changes in the terrain, resulting in a sub-optimal spraying process. To overcome these limitations, we propose to use a laser scanner, attached to the front of the sprayer's cabin, to scan the ground surface in front of the vehicle and to build a scrolling 3d map of the terrain. We evaluate the proposed solution in a series of field tests, demonstrating that the approach provides a more detailed and accurate representation of the environment than the current sonar-based solution, and which can lead to the development of more efficient boom control systems

A theoretical view on concept mapping

Auto‐monitoring is the pivotal concept in understanding the operation of concept maps, which have been used to help learners make sense of their study and plan learning activities. Central to auto‐monitoring is the idea of a ‘learning arena’ where individuals can manipulate concept representations and engage in the processes of checking, resolving and confirming understandings. The learner is assisted by familiar metaphors (for example, networks) and the possibility of thinking ‘on action’ while ‘in action’. This paper discusses these concepts, and concludes by arguing that maps are part of the process of learning rather than a manifestation of learning itself. Auto‐monitoring is suggested as an appropriate term to describe the process of engaging in the learning arena

Dynamic Motion Modelling for Legged Robots

An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the need to manually design the form of a motion model, and provides a direct means of incorporating auxiliary sensory data into the model. This representation and its accompanying algorithms are validated experimentally using an 8-legged kinematically complex robot, as well as a standard benchmark dataset. The presented method not only learns the robot's motion model, but also improves the model's accuracy by incorporating information about the terrain surrounding the robot

Snow avalanche susceptibility in the eastern hillside of the Aramo Range (Asturian Central Massif, Cantabrian Mountains, NW Spain)

A detailed snow avalanche susceptibility map of the eastern hillside in the Aramo Range (Cantabrian Mountains) is presented at a scale of 1:25,000. The Aramo Range is one of the major middle-altitude mountains of the Asturian Central Massif. Although it has of moderate height (maximum altitude of 1791 m a.s.l.), its eastern slope presents unusual snow avalanche activity. Specifically, a hundred of snow avalanche tracks have been mapped based on meticulous fieldwork and supported by interviews with local people, searches in newspaper archives, photointerpretation, and calculations based on the digital terrain model and geographic information system. As a result, a susceptibility map has been elaborated, which shows the suitability of combining fieldwork and geographic information technology. The composition consists of two maps that detail how the susceptibility mapping is obtained. The section analysed is limited to the eastern slope of the Aramo Range, whose total surface area is 1555.62 ha

2D Unsteady Routing and Flood Inundation Mapping for Lower Region of Brazos River Watershed

Present study uses two dimensional flow routing capabilities of hydrologic engineering center\u27s river analysis system (HEC-RAS) for flood inundation mapping in lower region of Brazo River watershed subjected to frequent flooding. For analysis, river reach length of 20 km located at Richmond, Texas, was considered. Detailed underlying terrain information available from digital elevation model of 1/9-arc second resolution was used to generate the two-dimensional (2D) flow area and flow geometrics. Streamflow data available from gauging station USGS08114000 was used for the full unsteady flow hydraulic modeling along the reach. Developed hydraulic model was then calibrated based on the manning\u27s roughness coefficient for the river reach by comparison with the downstream rating curve. Corresponding water surface elevation and velocity distribution obtained after 2D hydraulic simulation were used to determine the extent of flooding. For this, RAS mapper\u27s capabilities of inundation mapping in HEC-RAS itself were used. Mapping of the flooded areas based on inflow hydrograph on each time step were done in RAS mapper, which provided the spatial distribution of flow. The results from this study can be used for flood management as well as for making land use and infrastructure development decisions