Measuring gas concentration and wind intensity in a turbulent wind tunnel with a mobile robot

This paper presents the measurement of gas concentration and wind intensity performed with a mobile robot in a custom turbulent wind tunnel designed for experimentation with customizable wind and gas leak sources. This paper presents the representation in different information layers of the measurements obtained in the turbulent wind tunnel under different controlled environmental conditions in order to describe the plume of the gas and wind intensities inside the experimentation chamber. The information layers have been generated from the measurements gathered by individual onboard gas and wind sensors carried out by an autonomous mobile robot. On the one hand, the assumption was that the size and cost of these specialized sensors do not allow the creation of a net of sensors or other measurement alternatives based on the simultaneous use of several sensors, and on the other hand, the assumption is that the information layers created will have application on the development and test of automatic gas source location procedures based on reactive or nonreactive algorithms

Airborne chemical sensing with mobile robots

Airborne chemical sensing with mobile robots has been an active research areasince the beginning of the 1990s. This article presents a review of research work in this field,including gas distribution mapping, trail guidance, and the different subtasks of gas sourcelocalisation. Due to the difficulty of modelling gas distribution in a real world environmentwith currently available simulation techniques, we focus largely on experimental work and donot consider publications that are purely based on simulations

An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search

Robots have been used to model nature, while nature in turn can contribute to the real-world artifacts we construct. One particular domain of interest is chemical search where a number of efforts are underway to construct mobile chemical search and localization systems. We report on a project that aims at constructing such a system based on our understanding of the pheromone communication system of the moth. Based on an overview of the peripheral processing of chemical cues by the moth and its role in the organization of behavior we emphasize the multimodal aspects of chemical search, i.e. optomotor anemotactic chemical search. We present a model of this behavior that we test in combination with a novel thin metal oxide sensor and custom build mobile robots. We show that the sensor is able to detect the odor cue, ethanol, under varying flow conditions. Subsequently we show that the standard model of insect chemical search, consisting of a surge and cast phases, provides for robust search and localization performance. The same holds when it is augmented with an optomotor collision avoidance model based on the Lobula Giant Movement Detector (LGMD) neuron of the locust. We compare our results to others who have used the moth as inspiration for the construction of odor robot

Plume Analysis and Detection

This work involves the design and implementation of a gas-sensing mobile robot as an experimental tool to reconstruct a carbon dioxide plume in real-time based on concentration gradient and local wind speed measurements. The autonomous robot, an iRobot Create 2, achieves navigation through an embedded micro-controller using on-board sensors and various sensor fusion methods. A mass flow controller and diffuser are used to dependably generate a plume that simulates a point source. A base station reconstructs the plume via a state estimator through data from the robot and transmits commands to guide it into spatial regions of interest. This method has applicability for unmanned vehicles tracking emissions of contaminants and their effects in the environment

Wind-independent estimation of gas source distance from transient features of metal oxide sensor signals

The intermittency of the instantaneous concentration of a turbulent chemical plume is a fundamental cue for estimating the chemical source distance using chemical sensors. Such estimate is useful in applications such as environmental monitoring or localization of fugitive gas emissions by mobile robots or sensor networks. However, the inherent low-pass filtering of metal oxide (MOX) gas sensors typically used in odor-guided robots and dense sensor networks due to their low cost, weight and size hinders the quantification of concentration intermittency. In this paper, we design a digital differentiator to invert the low-pass dynamics of the sensor response, thus obtaining a much faster signal from which the concentration intermittency can be effectively computed. Using a fast photo-ionization detector as a reference instrument, we demonstrate that the filtered signal is a good approximation of the instantaneous concentration in a real turbulent plume. We then extract transient features from the filtered signal the so-called ''bouts'' to predict the chemical source distance, focusing on the optimization of the filter parameters and the noise threshold to make the predictions robust against changing wind conditions. This represents an advantage over previous bout-based models which require wind measurements typically taken with expensive and bulky anemometers to produce accurate predictions. The proposed methodology is demonstrated in a wind tunnel scenario where a MOX sensor is placed at various distances downwind of an emitting chemical source and the wind speed varies in the range 10-34 cm/s. The results demonstrate that models optimized with our methodology can provide accurate source distance predictions at different wind speeds

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Environmental Monitoring using Autonomous Vehicles: A Survey of Recent Searching Techniques

Autonomous vehicles are becoming an essential tool in a wide range of environmental applications that include ambient data acquisition, remote sensing, and mapping of the spatial extent of pollutant spills. Among these applications, pollution source localization has drawn increasing interest due to its scientific and commercial interest and the emergence of a new breed of robotic vehicles capable of performing demanding tasks in harsh environments without human supervision. In this task, the aim is to find the location of a region that is the source of a given substance of interest (e.g. a chemical pollutant at sea or a gas leakage in air) using a group of cooperative autonomous vehicles. Motivated by fast paced advances in this challenging area, this paper surveys recent advances in searching techniques that are at the core of environmental monitoring strategies using autonomous vehicles

Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping

This paper describes the development and validation of the currently smallest aerial platform with olfaction capabilities. The developed Smelling Nano Aerial Vehicle (SNAV) is based on a lightweight commercial nano-quadcopter (27 g) equipped with a custom gas sensing board that can host up to two in situ metal oxide semiconductor (MOX) gas sensors. Due to its small form-factor, the SNAV is not a hazard for humans, enabling its use in public areas or inside buildings. It can autonomously carry out gas sensing missions of hazardous environments inaccessible to terrestrial robots and bigger drones, for example searching for victims and hazardous gas leaks inside pockets that form within the wreckage of collapsed buildings in the aftermath of an earthquake or explosion. The first contribution of this work is assessing the impact of the nano-propellers on the MOX sensor signals at different distances to a gas source. A second contribution is adapting the 'bout' detection algorithm, proposed by Schmuker et al. (2016) to extract specific features from the derivative of the MOX sensor response, for real-time operation. The third and main contribution is the experimental validation of the SNAV for gas source localization (GSL) and mapping in a large indoor environment (160 m²) with a gas source placed in challenging positions for the drone, for example hidden in the ceiling of the room or inside a power outlet box. Two GSL strategies are compared, one based on the instantaneous gas sensor response and the other one based on the bout frequency. From the measurements collected (in motion) along a predefined sweeping path we built (in less than 3 min) a 3D map of the gas distribution and identified the most likely source location. Using the bout frequency yielded on average a higher localization accuracy than using the instantaneous gas sensor response (1.38 m versus 2.05 m error), however accurate tuning of an additional parameter (the noise threshold) is required in the former case. The main conclusion of this paper is that a nano-drone has the potential to perform gas sensing tasks in complex environments

Design and Implementation of a Mobile Robot for Carbon Monoxide Monitoring

The gas detection problem is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. The mobile robot used for gas detection has several advantages and can reduce danger for humans. In this study, we proposed an integration system for a mobile robot that can be used for carbon monoxide (CO) monitoring with different operating temperatures. The design and implementation of a mobile robot system that proposed consists of the onboard and ground stations. The proposed system can read CO gas concentration and temperature then send it wirelessly using an XBee module to the ground station. This system was also able to receive the command from the ground station to move the robot. The system provided real-time acquisition data that believed can be a useful tool for monitoring and can be applied for various purposes. The experimental results show that a combination of a mobile robot and environmental sensors can be used for environmental monitoring

Index to 1986 NASA Tech Briefs, volume 11, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1986 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences