Information Acquisition with Sensing Robots: Algorithms and Error Bounds

Utilizing the capabilities of configurable sensing systems requires addressing difficult information gathering problems. Near-optimal approaches exist for sensing systems without internal states. However, when it comes to optimizing the trajectories of mobile sensors the solutions are often greedy and rarely provide performance guarantees. Notably, under linear Gaussian assumptions, the problem becomes deterministic and can be solved off-line. Approaches based on submodularity have been applied by ignoring the sensor dynamics and greedily selecting informative locations in the environment. This paper presents a non-greedy algorithm with suboptimality guarantees, which does not rely on submodularity and takes the sensor dynamics into account. Our method performs provably better than the widely used greedy one. Coupled with linearization and model predictive control, it can be used to generate adaptive policies for mobile sensors with non-linear sensing models. Applications in gas concentration mapping and target tracking are presented.Comment: 9 pages (two-column); 2 figures; Manuscript submitted to the 2014 IEEE International Conference on Robotics and Automatio

Functional description of a terrestrial-aerial robot to detect and mark dangerous areas

There is an urgent need for a quick and effective survey of areas hit by accidents, that result in contamination with chemical, radioactive or explosive materials. Hence the need for mobile robots, which should be able to perform tasks in different environments for a long period of time, so that they can detect hazardous materials, identify their sources and create maps of their distribution. As a result, we can limit the spread of dangerous materials to other areas and reduce their harmful effects on the environment and the health of people. In this paper, we present a functional description of a robot capable of terrestrial-aerial movement in order to inspect areas and mark the contaminated parts. Here, we focus on the following topics: drone basic components, communications between the robot and the workstation, robot positioning, and detection of chemical contamination. During that we present a review of many important contributions in order to show the latest developments and try to explore future research directions

GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Numerical fluid dynamics simulation for drones’ chemical detection

The risk associated with chemical, biological, radiological, nuclear, and explosive (CBRNe) threats in the last two decades has grown as a result of easier access to hazardous materials and agents, potentially increasing the chance for dangerous events. Consequently, early detection of a threat following a CBRNe event is a mandatory requirement for the safety and security of human operators involved in the management of the emergency. Drones are nowadays one of the most advanced and versatile tools available, and they have proven to be successfully used in many different application fields. The use of drones equipped with inexpensive and selective detectors could be both a solution to improve the early detection of threats and, at the same time, a solution for human operators to prevent dangerous situations. To maximize the drone’s capability of detecting dangerous volatile substances, fluid dynamics numerical simulations may be used to understand the optimal configuration of the detectors positioned on the drone. This study serves as a first step to investigate how the fluid dynamics of the drone propeller flow and the different sensors position on-board could affect the conditioning and acquisition of data. The first consequence of this approach may lead to optimizing the position of the detectors on the drone based not only on the specific technology of the sensor, but also on the type of chemical agent dispersed in the environment, eventually allowing to define a technological solution to enhance the detection process and ensure the safety and security of first responders

Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots.

The ability to sense airborne pollutants with mobile robots provides a valuable asset for domains such as industrial safety and environmental monitoring. Oftentimes, this involves detecting how certain gases are spread out in the environment, commonly referred to as a gas distribution map, to subsequently take actions that depend on the collected information. Since the majority of gas transducers require physical contact with the analyte to sense it, the generation of such a map usually involves slow and laborious data collection from all key locations. In this regard, this paper proposes an efficient exploration algorithm for 2D gas distribution mapping with an autonomous mobile robot. Our proposal combines a Gaussian Markov random field estimator based on gas and wind flow measurements, devised for very sparse sample sizes and indoor environments, with a partially observable Markov decision process to close the robot’s control loop. The advantage of this approach is that the gas map is not only continuously updated, but can also be leveraged to choose the next location based on how much information it provides. The exploration consequently adapts to how the gas is distributed during run time, leading to an efficient sampling path and, in turn, a complete gas map with a relatively low number of measurements. Furthermore, it also accounts for wind currents in the environment, which improves the reliability of the final gas map even in the presence of obstacles or when the gas distribution diverges from an ideal gas plume. Finally, we report various simulation experiments to evaluate our proposal against a computer-generated fluid dynamics ground truth, as well as physical experiments in a wind tunnel.Partial funding for open access charge: Universidad de Málag

Cooperative strategies for the detection and localization of odorants with robots and artificial noses

En este trabajo de investigación se aborda el diseño de una plataforma robótica orientada a la implementación de estrategias de búsqueda cooperativa bioinspiradas. En particular, tanto el proceso de diseño de la parte electrónica como hardware se han enfocado hacia la validación en entornos reales de algoritmos capaces de afrontar problemas de búsqueda con incertidumbre, como lo es la búsqueda de fuentes de olor que presentan variación espacial y temporal. Este tipo de problemas pueden ser resueltos de forma más eficiente con el empleo de enjambres con una cantidad razonable de robots, y por tanto la plataforma ha sido desarrollada utilizando componentes de bajo coste. Esto ha sido posible por la combinación de elementos estandarizados -como la placa controladora Arduino y otros sensores integrados- con piezas que pueden ser fabricadas mediante una impresora 3D atendiendo a la filosofía del hardware libre (open-source). Entre los requisitos de diseño se encuentran además la eficiencia energética -para maximizar el tiempo de funcionamiento de los robots-, su capacidad de posicionamiento en el entorno de búsqueda, y la integración multisensorial -con la inclusión de una nariz electrónica, sensores de luminosidad, distancia, humedad y temperatura, así como una brújula digital-. También se aborda el uso de una estrategia de comunicación adecuada basada en ZigBee. El sistema desarrollado, denominado GNBot, se ha validado tanto en los aspectos de eficiencia energética como en sus capacidades combinadas de posicionamiento espacial y de detección de fuentes de olor basadas en disoluciones de etanol. La plataforma presentada -formada por el GNBot, su placa electrónica GNBoard y la capa de abstracción software realizada en Python- simplificará por tanto el proceso de implementación y evaluación de diversas estrategias de detección, búsqueda y monitorización de odorantes, con la estandarización de enjambres de robots provistos de narices artificiales y otros sensores multimodales.This research work addresses the design of a robotic platform oriented towards the implementation of bio-inspired cooperative search strategies. In particular, the design processes of both the electronics and hardware have been focused towards the real-world validation of algorithms that are capable of tackling search problems that have uncertainty, such as the search of odor sources that have spatio-temporal variability. These kind of problems can be solved more efficiently with the use of swarms formed by a considerable amount of robots, and thus the proposed platform makes use of low cost components. This has been possible with the combination of standardized elements -as the Arduino controller board and other integrated sensors- with custom parts that can be manufactured with a 3D printer attending to the open-source hardware philosophy. Among the design requirements is the energy efficiency -in order to maximize the working range of the robots-, their positioning capability within the search environment, and multiple sensor integration -with the incorporation of an artificial nose, luminosity, distance, humidity and temperature sensors, as well as an electronic compass-. Another subject that is tackled is the use of an efficient wireless communication strategy based on ZigBee. The developed system, named GNBot, has also been validated in the aspects of energy efficiency and for its combined capabilities for autonomous spatial positioning and detection of ethanol-based odor sources. The presented platform -formed by the GNBot, the GNBoard electronics and the abstraction layer built in Python- will thus simplify the processes of implementation and evaluation of various strategies for the detection, search and monitoring of odorants with conveniently standardized robot swarms provided with artificial noses and other multimodal sensors

Towards UAV-assisted monitoring of onshore geological CO2 storage site

Scientists all over the world look for solutions to reduce greenhouse gas emissions in an effort to achieve proclaimed emissions reduction targets. An intriguing candidate with the potential to make a substantial contribution to this attempt is carbon capture and storage (CCS). The key advantage of CCS is that it provides the possibility to make a significant impact on the reduction of anthropogenic carbon dioxide (CO2) emissions from power plants and carbon-rich industry processes while maintaining existing fossil fuel energy infrastructure. The technique could therefore be used as a transitional solution until fossil fuels can be eliminated from the energy generation mix, and the energy efficiency of industrial processes as well as appliances and products is further improved. Like other technologies, CCS comes with its risks and rewards. To minimize possible negative impacts on humans as well as on the environment, it is necessary to understand the risks and to address them accordingly. A range of monitoring solutions for geological CO2 storage sites is available. However, a cost-effective solution for the regular observation of atmospheric CO2 concentrations (or tracer concentrations) of large areas above onshore geological CO2 storage sites has yet to be developed. This thesis discusses the use of a helicopter unmanned aerial vehicle (UAV) to fill this gap. The robot platform and its autopilot are designed to cope with ongoing sensor developments in addition to providing safety features necessary for the beyond line-of-sight operation of the UAV. The design focuses on the use of commercial off-the-shelf components for the aerial platform in order to shorten the development time and to reduce costs. The autopilot does neither enforce a specific helicopter model nor defines a set position estimation unit to be used. Access to the control loop enables low-level extensions like obstacle avoidance to be implemented. The developed solution allows the monitoring of an area of approximately 750m2 with one set of batteries in one altitude with a spatial resolution of 2m by 2m. Experiments show that point source leaks of as low as 100kg CO2 per day can be detected and their source located. As opposed to autonomous take-offs of the helicopter UAV, autonomous landings on small dedicated helipads require an accurate localization system. A time difference of arrival (TDOA) based acoustic localization system which is based on planar microphone arrays with at least four microphones is proposed. The system can be embedded into the landing platform and provides the accuracy necessary to land the UAV on a helipad of the size of 1m by 1m. A review of existing TDOA-based approaches is given. Simulations show that the developed approach outperforms its direct competitors for the targeted task. Furthermore, experimental results with the developed UAV confirm the feasibility of the introduced method. The effects of the sensor arrangement onto the quality of the calculated position estimates are also discussed. In order to combine robotic-assisted monitoring solutions and other monitoring strategies (e.g. sensor networks and individual sensors) into a single solution, it is necessary to have a framework which allows next to the measurement data analysis also the management (path changes, robot behavior changes, monitoring of internal robot state) of possibly multiple heterogeneous mobile robotic systems. A modular user interface (UI) framework is proposed which allows robots from different vendors and with various configurations next to individual sensors and sensor networks to be managed from a single application. The software system introduces a strict separation between the robot control software and UIs. UI implementations inside the UI framework can be reused across robot platforms, which can reduce the integration time of new robots significantly. The end user benefits by being able to manage a fleet of robots from various vendors and being able to analyze all the measurement data together in a single solution