On localisation with robust power control for safety critical wireless sensor networks

A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots.A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Communication for Teams of Networked Robots

There are a large class of problems, from search and rescue to environmental monitoring, that can benefit from teams of mobile robots in environments where there is no existing infrastructure for inter-agent communication. We seek to address the problems necessary for a team of small, low-power, low-cost robots to deploy in such a way that they can dynamically provide their own multi-hop communication network. To do so, we formulate a situational awareness problem statement that specifies both the physical task and end-to-end communication rates that must be maintained. In pursuit of a solution to this problem, we address topics ranging from the modeling of point-to-point wireless communication to mobility control for connectivity maintenance. Since our focus is on developing solutions to these problems that can be experimentally verified, we also detail the design and implantation of a decentralized testbed for multi-robot research. Experiments on this testbed allow us to determine data-driven models for point-to-point wireless channel prediction, test relative signal-strength-based localization methods, and to verify that our algorithms for mobility control maintain the desired instantaneous rates when routing through the wireless network. The tools we develop are integral to the fielding of teams of robots with robust wireless network capabilities

Wireless sensor systems in indoor situation modeling II (WISM II)

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Propagation, Localization and Navigation in Tunnel-like Environments

La robótica de servicio, entendida como aquella destinada al uso de uno o varios robots con fines de, por ejemplo, vigilancia, rescate e inspecciones, ha ido tomando cada vez más relevancia en los últimos años. Debido a los grandes avances en las distintas áreas de la robótica, los robots han sido capaces de ejecutar satisfactoriamente tareas que resultan peligrosas o incluso imposibles para los humanos, en diversos entornos. Entre ellos, los entornos confinados como túneles, minas y tuberías, han atraído la atención en aplicaciones relacionadas con transporte ferroviario, redes vehiculares, búsqueda y rescate, y vigilancia, tanto en el ámbito civil como militar. En muchas tareas, la utilización de varios robots resulta más provechoso que utilizar sólo uno. Para cooperar, los robots deben intercambiar información sobre el entorno y su propio estado, por lo que la comunicación entre ellos resulta crucial. Debido a la imposibilidad de utilizar redes cableadas entre robots móviles, se despliegan redes inalámbricas. Para determinar la calidad de señal entre dos robots, inicialmente se utilizaban modelos de propagación basados únicamente en la distancia entre ellos. Sin embargo, estas predicciones sólo resultan útiles en exteriores y sin la presencia de obstáculos, que sólo componen una pequeña parte de los escenarios de la robótica de servicio. Mas aún, la naturaleza altamente multi-trayecto de la propagación electromagnética en túneles hace que éstos actúen como guías de onda para cierto rango de frecuencias, extendiendo considerablemente el alcance de comunicación en comparación con entornos exteriores. Sin embargo, la señal se ve afectada con profundos desvanecimientos (llamados fadings en inglés). Esto los convierte en un reto para la robótica que considera la comunicación entre robots como fundamental. Además, la naturaleza hostil de estos entornos, así como también la falta de características visuales y estructurales, dificultan la localización en estos escenarios, cuestión que resulta fundamental para ejecutar con éxito una tarea con un robot. Los métodos de localización utilizados en interiores, como aquellos basados en SLAM visual, resultan imprecisos por la falta de características distintivas para cámaras o lásers, mientras que los sensores utilizados en exteriores, como el GPS, no funcionan dentro de túneles o tuberías. En esta tesis abordamos problemas fundamentales para la robótica con el fin de proporcionar herramientas necesarias para la exploración con robots en entornos tipo túnel, manteniendo la conectividad de la red de comunicaciones formada por varios robots y una estación base. Para ello, primeramente caracterizamos, en términos de propagación, los dos escenarios tipo túnel más comunes: un túnel de hormigón y una tubería metálica. Hacemos énfasis en el fenómeno de los fadings, ya que son el problema más importante a considerar para mantener la comunicación. Posteriormente presentamos una estrategia de navegación para desplegar un equipo de robots en un túnel, lidiando con los fadings para mantener la conectividad de la red formada por los robots. Esta estrategia ha sido validada a través de numerosos experimentos realizados en un túnel real, el túnel de Somport. Luego, abordamos el problema de la localización, proponiendo e implementando una técnica que permite estimar la posición de un robot dentro de una tubería, basada en la periodicidad de los fadings. El método es validado a través de experimentos reales en tuberías de pequeña y grandes dimensiones. Finalmente, proponemos esquemas de diversidad espacial, de forma que se facilita la navegación mientras se mejora la localización.Deploying a team of robots for search and rescue, inspection, or surveillance, has increasingly gained attention in the last years. As a result of the advances in several areas of robotics, robots have been able to successfully execute tasks that are hazardous or even impossible for humans in a variety of scenarios, such as outdoors, indoors, or even underground. Among these scenarios, tunnel-like environments (such as tunnels, mines, or pipes) have attracted attention for train applications, vehicular networks, search and rescue, and even service and surveillance missions in both military and civilian contexts. In most of the tasks, utilizing a multi-robot team yields better results than a singlerobot system, as it makes the system more robust while reducing the time required to complete tasks. In order to cooperate, robots must exchange information about their current state and the surrounding environment, making communication between them a crucial task. However, due to the mobile nature of robots used for exploration, a wired architecture is not possible nor convenient. Instead, a wireless network is often deployed. Wireless propagation in tunnel-like environments, characterized for the presence of strong fading phenomena, differs from regular indoor and outdoor scenarios, posing multiple challenges for communication-aware robotics. In addition, accurate localization is a problem in environments such as tunnels or pipes. These environments generally lack distinctive visual and/or structural features and are longer than they are wide in shape. Standard indoor localization techniques do not perform well in pipelines or tunnels given the lack of exploitable features, while outdoor techniques (GPS in particular) do not work in these scenarios. In this thesis, we address basic robotics-related problems in order to provide some tools necessary for robotics exploration in tunnel-like scenarios under connectivity constraints. In the first part, we characterize, in terms of propagation, two of the most common tunnel-like environments: a pipe and a tunnel. We emphasize the spatial-fadings phenomena, as it is one of the most relevant issues to deal with, in a communications context. Secondly, we present a navigation strategy to deploy a team of robots for tunnel exploration, in particular maintaining network connectivity in the presence of these fadings. Several experiments conducted in a tunnel allow us to validate the connectivity maintenance of the system. Next, we address the localization problem and propose a technique that uses the periodicity of the fadings to estimate the position of the robots from the base station. The method is validated in small-scale and large-scale pipes. Finally, we propose spatial diversity schemes in order to ease the navigation while improving the localization

MIMO In Vivo

We present the performance of MIMO for in vivo environments, using ANSYS HFSS and their complete human body model, to determine the maximum data rates that can be achieved using an IEEE 802.11n system. Due to the lossy nature of the in vivo medium, achieving high data rates with reliable performance will be a challenge, especially since the in vivo antenna performance is strongly affected by near field coupling to the lossy medium and the signals levels will be limited by specified specific absorption rate (SAR) levels. We analyzed the bit error rate (BER) of a MIMO system with one pair of antennas placed in vivo and the second pair placed inside and outside the body at various distances from the in vivo antennas. The results were compared to SISO simulations and showed that by using MIMO in vivo, significant performance gain can be achieved, and at least two times the data rate can be supported with SAR limited transmit power levels, making it possible to achieve target data rates in the 100 Mbps.Comment: WAMICON 201

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Online Mapping and Perception Algorithms for Multi-robot Teams Operating in Urban Environments.

This thesis investigates some of the sensing and perception challenges faced by multi-robot teams equipped with LIDAR and camera sensors. Multi-robot teams are ideal for deployment in large, real-world environments due to their ability to parallelize exploration, reconnaissance or mapping tasks. However, such domains also impose additional requirements, including the need for a) online algorithms (to eliminate stopping and waiting for processing to finish before proceeding) and b) scalability (to handle data from many robots distributed over a large area). These general requirements give rise to specific algorithmic challenges, including 1) online maintenance of large, coherent maps covering the explored area, 2) online estimation of communication properties in the presence of buildings and other interfering structure, and 3) online fusion and segmentation of multiple sensors to aid in object detection. The contribution of this thesis is the introduction of novel approaches that leverage grid-maps and sparse multi-variate gaussian inference to augment the capability of multi-robot teams operating in urban, indoor-outdoor environments by improving the state of the art of map rasterization, signal strength prediction, colored point cloud segmentation, and reliable camera calibration. In particular, we introduce a map rasterization technique for large LIDAR-based occupancy grids that makes online updates possible when data is arriving from many robots at once. We also introduce new online techniques for robots to predict the signal strength to their teammates by combining LIDAR measurements with signal strength measurements from their radios. Processing fused LIDAR+camera point clouds is also important for many object-detection pipelines. We demonstrate a near linear-time online segmentation algorithm to this domain. However, maintaining the calibration of a fleet of 14 robots made this approach difficult to employ in practice. Therefore we introduced a robust and repeatable camera calibration process that grounds the camera model uncertainty in pixel error, allowing the system to guide novices and experts alike to reliably produce accurate calibrations.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113516/1/jhstrom_1.pd