Towards Odor-Sensitive Mobile Robots

J. Monroy, J. Gonzalez-Jimenez, "Towards Odor-Sensitive Mobile Robots", Electronic Nose Technologies and Advances in Machine Olfaction, IGI Global, pp. 244--263, 2018, doi:10.4018/978-1-5225-3862-2.ch012 Versión preprint, con permiso del editorOut of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical ones when operating in real environments. Until now, these sensorial systems mostly relied on range sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely been employed, they can provide a complementary sensory information, vital for some applications, as with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities and also reviews some of the hurdles that are preventing smell from achieving the importance of other sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status on the three main fields within robotics olfaction: the classification of volatile substances, the spatial estimation of the gas dispersion from sparse measurements, and the localization of the gas source within a known environment

Environmental Dynamics in Animal Waste Reclamation in the Scaling up of Livestock in Thailand

Thailand has seen a scaling up of pig production in numbers and structure. Nonetheless, in-house separation and agricultural reclamation of pig solid waste are common practice. Waste reclamation is not taking place under small-scale farming and its environmental dynamics cannot be simply understood as a direct projection to larger scales. Scaling up has transformed the environmental significance of waste reclamation, including waste transfer from livestock to agriculture farmers. Waste transfer benefits pig farmers by trade and removal of waste by agriculture and aquaculture farmers and is key to the environmental dynamics of pig production. However, waste reclamation is not clearly defined as a management option in environmental frameworks. Waste management is mainly addressed as in-farm wastewater with limited attention to agro-environmental values of present practices. To recognise present practices in agro-environmental policies this thesis suggests a descriptive strategy focused on the transfer of waste. Such strategy would avoid command-and-control norms, avoid conflicting with an environmental culture centered in biogas technology and support knowledge transfer in agriculture. A focus on waste transfer from animal farms to agriculture [and aquaculture] plots is interpreted as off-site waste management. Off-site waste management calls for the inclusion of geographical variables beyond animal farms. This leads to an extended area of environmental influence (EAEI). Resulting environmental dynamics allows an interpretation of environment beyond resource in classical agricultural geography to a connotation where environment is also significant to agriculture and livestock because of the impacts from production. The recognition of reclamation practices and, consequently, of the integral environmental dynamics, and hence the connotation of environment, would contribute to connect livestock with agriculture through environmental geography. Intensive livestock is then defined as distribution and not location. Formalisation of reclamation practices entails the acknowledgment of agro-ecological cycles in livestock

Measuring the Muon Content of Air Showers with IceTop

IceTop, the surface component of the IceCube detector, has been used to measure the energy spectrum of cosmic ray primaries in the range between 1.58 PeV and 1.26 EeV. It can also be used to study the low energy muons in air showers by looking at large distances (> 300m) from the shower axis. We will show the muon lateral distribution function at large lateral distances as measured with IceTop and discuss the implications of this measurement. We also discuss the prospects for low energy muon studies with IceTop.Comment: 5 pages, 9 figures, presented at the 18th meeting of the International Symposium on Very High Energy Cosmic Ray Interactions (ISVHECRI 2014

Real-Time odor classification through sequential bayesian filtering

The classification of volatiles substances with an e-nose is still a challenging problem, particularly when working under real-time, out-of-the-lab environmental conditions where the chaotic and highly dynamic characteristics of the gas transportation induce an almost permanent transient state in the e-nose readings. In this work, a sequential Bayesian filtering approach is proposed to efficiently integrate information from previous e-nose observations while updating the belief about the gas class on a real-time basis. We validate our proposal with two real olfaction datasets composed of dynamic time-series experiments (gas transitions are Considered, but no mixture of gases), showing an improvement in the classification rate when compared to a stand-alone probabilistic classifier.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Gas Source Localization Strategies for Teleoperated Mobile Robots. An Experimental Analysis

Gas source localization (GSL) is one of the most important and direct applications of a gas sensitive mobile robot, and consists in searching for one or multiple volatile emission sources with a mobile robot that has improved sensing capabilities (i.e. olfaction, wind flow, etc.). This work adresses GSL by employing a teleoperated mobile robot, and focuses on which search strategy is the most suitable for this teleoperated approach. Four different search strategies, namely chemotaxis, anemotaxis, gas-mapping, and visual-aided search, are analyzed and evaluated according to a set of proposed indicators (e.g. accuracy, efficiency, success rate, etc.) to determine the most suitable one for a human-teleoperated mobile robot. Experimental validation is carried out employing a large dataset composed of over 150 trials where volunteer operators had to locate a gas-leak in a virtual environment under various and realistic environmental conditions (i.e. different wind flow patterns and gas source locations). We report different findings, from which we highlight that, against intuition, visual-aided search is not always the best strategy, but depends on the environmental conditions and the operator’s ability to understand how gas distributes.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach

In this paper we present a fast and precise method to estimate the planar motion of a lidar from consecutive range scans. For every scanned point we formulate the range flow constraint equation in terms of the sensor velocity, and minimize a robust function of the resulting geometric constraints to obtain the motion estimate. Conversely to traditional approaches, this method does not search for correspondences but performs dense scan alignment based on the scan gradients, in the fashion of dense 3D visual odometry. The minimization problem is solved in a coarse-to-fine scheme to cope with large displacements, and a smooth filter based on the covariance of the estimate is employed to handle uncertainty in unconstraint scenarios (e.g. corridors). Simulated and real experiments have been performed to compare our approach with two prominent scan matchers and with wheel odometry. Quantitative and qualitative results demonstrate the superior performance of our approach which, along with its very low computational cost (0.9 milliseconds on a single CPU core), makes it suitable for those robotic applications that require planar odometry. For this purpose, we also provide the code so that the robotics community can benefit from it.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish Government under project DPI2014-55826-R and the grant program FPI-MICINN 2012

Locally linear approximation for Kernel methods : the Railway Kernel

In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capability of the proposed kernel is higher than the obtained using RBF kernels. Experimental work is shown to support the theoretical issues.Support vector machines, Kernel Methods, Classification problems