Inventory of wetland habitat using remote sensing for the proposed Oahe irrigation unit in eastern South Dakota

An inventory of wetlands for the area included in the proposed Oahe irrigation project was conducted to provide supplemental data for the wildlife mitigation plan. Interpretation techniques for inventoring small wetlands in the low relief terrain of the Lake Dakota Plain were documented and data summaries included. The data were stored and tabulated in a computerized spatial data analysis system

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of westland habitat in eastern South Dakota, parts 1 and 2

The author has identified the following significant results. LANDSAT fulfilled the requirements for general soils and land use information. RB-57 imagery was required to provide the information and detail needed for mapping soils for land evaluation. Soils maps for land evaluation were provided on clear mylar at the scale of the county highway map to aid users in locating mapping units. Resulting mapped data were computer processed to provided a series of interpretive maps (land value, limitations to development, etc.) and area summaries for the users

Probabilistic Maximum Set Cover with Path Constraints for Informative Path Planning

We pose a new formulation for informative path planning problems as a generalisation of the well-known maximum set cover problem. This new formulation adds path constraints and travel costs, as well as a probabilistic observation model, to the maximum set cover problem. Our motivation is informative path planning applications where the observation model can be naturally encoded as overlapping subsets of a set of discrete elements. These elements may include features, landmarks, regions, targets or more abstract quantities, that the robot aims to observe while moving through the environment with a given travel budget. This formulation allows directly modelling the dependencies of observations from different viewpoints. We show this problem is NP-hard and propose a branch and bound tree search algorithm. Simulated experiments empirically evaluate the bounding heuristics, several tree expansion policies and convergence rate towards optimal. The tree pruning allows finding optimal or bounded-approximate solutions in a reasonable amount of time, and therefore indicates our work is suitable for practical applications

Secado natural de yuca para la alimentacion animal: Una nueva agroindustria en Colombia

A collaborative project of the Colombian Integrated Rural Development Program (DRI) and CIAT, aimed at establishing small agroindustrial firms to produce dry cassava on the Atlantic Coast of Colombia, is described. It began with the installation of a pilot plant for natural drying of cassava, with the collaboration of a group of 15 farmers. This plant operated on an exptl. basis in 1981 to obtain information about the efficiency of the process under the conditions existing on the Colombian Atlantic Coast and to determine the product`s acceptability by the animal feed industry. In 1982, during the project`s 2nd phase, the pilot plant was operated semicommercially to obtain data on production costs; likewise, it showed the economical and technical feasibility of the process. In 1983, the 3rd phase began, consisting in the replication of the project in other cassava-producing areas of the region. In 1984 and 1985, the project grew considerably, with 20 drying plants functioning in 1984 and 36 in 1985. To establish small-scale natural cassava drying plants, the following requisites are essential: (1) selection of a processing technology that can be assimilated, controlled, and easily managed by farmers; (2) implementation of integrated programs of processing, production, and commercialization that reduce the risks and increase net incomes of farmers; and (3) provision of institutional support that is adequate in terms of technical assistance, credit facilities, management and fiscal training, and of advice in the formation and consolidation of cooperative and associative groups for agricultural production. (AS-CIAT

Path planning with spatiotemporal optimal stopping for stochastic mission monitoring

© 2017 IEEE. We consider an optimal stopping formulation of the mission monitoring problem, in which a monitor vehicle must remain in close proximity to an autonomous robot that stochastically follows a predicted trajectory. This problem arises in a diverse range of scenarios, such as autonomous underwater vehicles supervised by surface vessels, pedestrians monitored by aerial vehicles, and animals monitored by agricultural robots. The key problem characteristics we consider are that the monitor must remain stationary while observing the robot, robot motion is modeled in general as a stochastic process, and observations are modeled as a spatial probability distribution. We propose a resolution-complete algorithm that runs in a polynomial time. The algorithm is based on a sweep-plane approach and generates a motion plan that maximizes the expected observation time and value. A variety of stochastic models may be used to represent the robot trajectory. We present results with data drawn from real AUV missions, a real pedestrian trajectory dataset and Monte Carlo simulations. Our results demonstrate the performance and behavior of our algorithm, and relevance to a variety of applications

Decentralised Mission Monitoring with Spatiotemporal Optimal Stopping

© 2018 IEEE. We consider a multi-robot variant of the mission monitoring problem. This problem arises in tasks where a robot observes the progress of another robot that is stochastically following a known trajectory, among other applications. We formulate and solve a variant where multiple tracker robots must monitor a single target robot, which is important because it enables the use of multi-robot systems to improve task performance in practice, such as in marine robotics missions. Our algorithm coordinates the behaviour of the trackers by computing optimal single-robot paths given a probabilistic representation of the other robots' paths. We employ a decentralised scheme that optimises over probability distributions of plans and has useful analytical properties. The planned trajectories collectively maximise the probability of observing the target throughout the mission with respect to probabilistic motion and observation models. We report simulation results for up to 8 robots that support our analysis and indicate that our algorithm is a feasible solution for improving the performance of mission monitoring systems

Online planning for multi-robot active perception with self-organising maps

© 2017, Springer Science+Business Media, LLC, part of Springer Nature. We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has a runtime complexity that is polynomial in the number of nodes to be observed and the magnitude of the relative weighting of rewards. We show empirically the runtime is sublinear in the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Exploration objectives for online tasks where the environment is only partially known in advance are modelled by introducing goal regions in unexplored space. Online replanning is performed efficiently by adapting previous solutions as new information becomes available. Simulations were performed using a 3D point-cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for online active perception tasks with continuous sets of candidate viewpoints and long planning horizons

Multi-robot path planning for budgeted active perception with self-organising maps

© 2016 IEEE. We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has polynomial-bounded runtime independent of the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Simulations were performed using a 3D point cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for budgeted active perception tasks with continuous sets of candidate viewpoints and long planning horizons

A short survey on nonlinear models of the classic Costas loop: rigorous derivation and limitations of the classic analysis

Rigorous nonlinear analysis of the physical model of Costas loop --- a classic phase-locked loop (PLL) based circuit for carrier recovery, is a challenging task. Thus for its analysis, simplified mathematical models and numerical simulation are widely used. In this work a short survey on nonlinear models of the BPSK Costas loop, used for pre-design and post-design analysis, is presented. Their rigorous derivation and limitations of classic analysis are discussed. It is shown that the use of simplified mathematical models, and the application of non rigorous methods of analysis (e.g., simulation and linearization) may lead to wrong conclusions concerning the performance of the Costas loop physical model.Comment: Accepted to American Control Conference (ACC) 2015 (Chicago, USA

Direct cross section measurement for the 18O(p,γ)19F reaction at astrophysical energies at LUNA

18 O ( p, γ ) 19 F plays an important role in the AGB star scenarios. The low energy cross section could be influenced by a hypothetical low energy resonance at 95 keV and by the tails of the higher energy broad states. The 95 keV resonance lies in the energy window corresponding to the relevant stellar temperature range of 40-50 MK.Measurements of the direct cross section were performed at the Laboratory for Underground Nuclear Astrophysics (LUNA), including the unobserved low energy resonance, the higher energy resonances and the non-resonant component, taking advantage of the extremely low environmental background. Here we report on the experimental setup and the status of the analysis