Dynamic Indoor Research Articles

Genetic diversity ofAspergillus fumigatusin indoor hospital environments

Environmental isolates of Aspergillus fumigatus are less studied than those recovered from clinical sources. In the present study, the genetic diversity among such environmental isolates was assessed, as well as their dispersion ability and the acquisition of new strains in 19 medical units of the same hospital. A. fumigatus isolates were genotyped using a single multiplex PCR-based reaction with eight microsatellite markers and an insertion/deletion polymorphism. A total of 130 unique genotypes were found among a total of 250 A. fumigatus isolates. Genotypic diversity ranged from 0.86 to 1 in samples from hospital rooms, and there was no correlation between these samples and the presence of high-efficiency particulate air filters or any other air filtration system. Four of the six most prevalent A. fumigatus strains were recovered from water samples. The occurrence of microvariation was common among environmental isolates, which affected each of the microsatellite markers. The assessment of the genetic diversity of A. fumigatus is a useful tool for illustrating the presence or absence of specific clonal populations in a clinical setting. A. fumigatus populations were highly dynamic indoors, and new populations were found in just a few months. Due to the high indoor dispersion capability of A. fumigatus, more attention should be given to strains with increased pathogenic potential or reduced susceptibility to anti-fungal drugs.

Dynamic indoor localization using multilateration with RSSI in wireless sensor networks for transport logistics

In this paper a novel localization approach in wireless sensor networks (WSNs) with spatial dynamic RSSI-filtering is presented. For the food transportation logistics WSNs could be applied to monitor the environmental parameters, e.g. temperature and humidity, within the container. The sensor nodes are arbitrarily distributed within the palettes. In a narrow and crammed environment like a closed container, it is difficult to achieve a direct positioning with Received Signal Strength Indicator (RSSI) due to the signal damping and reflection. The proposed approach exploits the movement of the sensor node during the loading process to compensate the reflection effect of the electromagnetic wave. In order to achieve a precise distance measurement with RSSI, a spatial dynamic RSSI-filter is applied in this work. The position of the sensor nodes is able to be already determined during the loading, thus neither additional hardware nor a further positioning process is required during the transportation process.

HERB: a home exploring robotic butler

We describe the architecture, algorithms, and experiments with HERB, an autonomous mobile manipulator that performs useful manipulation tasks in the home. We present new algorithms for searching for objects, learning to navigate in cluttered dynamic indoor scenes, recognizing and registering objects accurately in high clutter using vision, manipulating doors and other constrained objects using caging grasps, grasp planning and execution in clutter, and manipulation on pose and torque constraint manifolds. We also present numerous severe real-world test results from the integration of these algorithms into a single mobile manipulator.

Safe Navigation of a Mobile Robot Considering Visibility of Environment

We present one approach to achieve safe navigation in an indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms possess fundamental limitations in that the robot can avoid only ldquovisiblerdquo ones among surrounded obstacles. In a real environment, it is not possible to detect all the dynamic obstacles around the robot. There are many occluded regions due to the limited field of view. In order to avoid collisions, it is desirable to exploit visibility information. This paper proposes a safe navigation scheme to reduce collision risk considering occluded dynamic obstacles. The robot's motion is controlled by the hybrid control scheme. The possibility of collision is dually reflected to path planning and speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The experimental results show that the robot moves along the safe path to obtain sufficient field of view. In addition, safe speed constraints are applied in motion control. It is experimentally verified that a robot safely navigates in dynamic indoor environment by adopting the proposed scheme.

ESD: a novel optimisation algorithm for positioning estimation of WSNs in GPS-denied environments – from simulation to experimentation

Over the last years, many novel applications have been envisaged for distributed Wireless Sensor Networks (WSNs) in the area of monitoring, communication and control. One of the key enabling services in WSNs is localisation, since the availability of nodes' location may represent the fundamental support for various protocols (e.g. routing) and applications (e.g. habitat monitoring). In this context, the contributions of our research work are as follows: (a) we will design Enhanced Steepest Descent (ESD), a novel distributed optimisation algorithm, which can be used for position computation, and will show, via computer-based simulations, that it turns out to outperform other well-known algorithms in terms of accuracy and complexity; (b) we will validate its suitability of an implementation onto commercially available WSNs platforms and will investigate, via experimental activities, the effects of network topology and ranging errors on its performance, in a realistic and dynamic indoor propagation environment.

Evaluation of position tracking technologies for user localization in indoor construction environments

Evolving technologies such as location-aware computing offer significant potential of improving important decision-making tasks on construction sites by providing support for tedious and time-consuming tasks associated with timely and accurate access to project information. For example, rapid and convenient access to contextual project information, through continuous position tracking of engineers, managers, and inspectors, can lead to significant cost and time savings due to the accuracy and immediacy with which relevant project information can be made available to field personnel. Considering the spatial expanse and dynamic nature of typical construction projects, mobile users need to be constantly tracked both outdoors as well as indoors. The Global Positioning System (GPS) is an attractive option for outdoor environments, but is not suitable for indoor applications because it needs a clear line-of-sight to orbital satellites in order to track position. As a result, alternate means of tracking users' location in indoor environments without relying on GPS is needed. This paper presents research that investigated the effectiveness of three wireless technologies for dynamic indoor user position tracking. In particular, Wireless Local Area Networks (WLAN), Ultra-Wide Band (UWB), and Indoor GPS positioning systems are evaluated and compared. Experimental results demonstrate the ability of Indoor GPS, in particular, to estimate a mobile user's location with relatively low uncertainty (1 to 2 cm).

Automated Bayesian network Integration based on Ontology for Reasoning Object Existence of Service Robot

Object detection of service robots is very important for their service. Most of services such as delivery, errand of users are related to objects. Conventional methods are based on the geometric models in static industrial environments, but they have limitations in uncertain and dynamic indoor environments, because interest object can be occluded or small in the image according to the robot's location or angle. For solving these uncertain situations, it is helpful to predict the probability of target object, because it can give important information for their next action. Our idea is to use observed objects as context information for predicting target one. For this, we adopt Bayesian networks and ontology together for modeling domain knowledge and reasoning objects in probabilistic frame. We verified the performance and process of our method through the experiments.

Fuzzy logic-based real-time robot navigation in unknown environment with dead ends

The proposed approach in this paper involves a new grid-based map model called “memory grid” and a new behavior-based navigation method called “minimum risk method”. The memory grid map records not only the environmental information, but also the robot experience. The minimum risk method is just one of the applications of the memory grid technique, which addresses the local minimum problem faced by a goal-oriented robot navigating in unknown indoor environments. The Minimum Risk implies that the robot is able to choose the safest region that can avoid colliding with obstacles and prevent the robot from iterating previous trajectory. This method is demonstrated to work in long wall, large concave, recursive U -shaped, unstructured, cluttered, maze-like, and dynamic indoor environments. It adopts a strategy of multi-behavior coordination in which a novel path-searching behavior is developed to recommend the region offering the minimum risk. Fuzzy logic is used to implement the behavior design and coordination. The proposed approach is verified with simulation and real-world tests.

Appearance-based localization for mobile robots using digital zoom and visual compass

This paper describes a localization system for mobile robots moving in dynamic indoor environments, which uses probabilistic integration of visual appearance and odometry information. The approach is based on a novel image matching algorithm for appearance-based place recognition that integrates digital zooming, to extend the area of application, and a visual compass. Ambiguous information used for recognizing places is resolved with multiple hypothesis tracking and a selection procedure inspired by Markov localization. This enables the system to deal with perceptual aliasing or absence of reliable sensor data. It has been implemented on a robot operating in an office scenario and the robustness of the approach is demonstrated experimentally.

An integrated modeling tool for simultaneous analysis of thermal performance and indoor air quality in buildings

To analyze the thermal performance and indoor air quality (IAQ) in building simultaneously and quickly, we have developed an integrated modeling tool to simulate the dynamic indoor multi-parameters distributions and concentrations. The tool can take the parameters including indoor temperature, indoor humidity, and pollutant concentrations (e.g., volatile organic compounds (VOC) CO 2, particulate matter (PM)), as well as the heating/cooling load of heating, ventilating, and air-conditioning (HVAC) system into account. It couples a new zonal approach based on room air age. This paper presents the basic concept and flow chart in developing the modeling tool, and demonstrates the tool's application in a hypothetical health care building. The tool could be used for design of HVAC system with IAQ control devices and for the simultaneous analysis of thermal performance and IAQ in buildings.

A New Solution to Map Dynamic Indoor Environments

In this paper, we propose a new algorithm of mapping dynamic indoor environments. Instead of accurate but expensive laser, we employ sonar and camera to map dynamic structured indoor environments. Based on fuzzy-tuned grid-based map (FTGBM), we use two methods: sonar temporal difference (STD) and statistical background subtraction (SBS), to detect and track moving objects when mapping dynamic environments. The former is a consistency-based method realized by monitoring a sequence of temporal lattice maps for a certain number of measurement periods to detect moving objects by using sonars; and the latter is a background subtraction technique which adopts an expectation maximization (EM) learned 3-class mixture of Gaussians to model the nonstationary background relied on sufficient update during mapping process. After finding the moving objects, we propose a fuzzy-tuned integration (FTI) method to incorporate the results of motion detection into the mapping process. The simulation and experiment demonstrate the capabilities of our approach.

Robustness of Visual Place Cells in Dynamic Indoor and Outdoor Environment

In this paper, a model of visual place cells (PCs) based on precise neurobiological data is presented. The robustness of the model in real indoor and outdoor environments is tested. Results show that the interplay between neurobiological modelling and robotic experiments can promote the understanding of the neural structures and the achievement of robust robot navigation algorithms. Short Term Memory (STM), soft competition and sparse coding are important for both landmark identification and computation of PC activities. The extension of the paradigm to outdoor environments has confirmed the robustness of the vision-based model and pointed to improvements in order to further foster its performance.

Investigations on effect of the orientation on thermal comfort in terraced housing in Malaysia

The design of residential buildings has a significant impact on people's daily life. The ‘terrace house’ form constitutes the majority of the residential building stock in Malaysia. The lack of thermal comfort in terrace houses is mainly due to the poor thermal properties of the building materials and to design factors [1]. The evaluation is derived from a series of computer simulations using commercially available software. This paper concentrates on analysing the effect of the orientation of the existing case of a typical terrace house in Malaysia by finding the dynamic indoor air temperature for each orientation. Copyright , Manchester University Press.

Dynamic Simulation Model of Indoor Wideband Directional Channels

Culled from existing channel measurements, a dynamic indoor wideband directional-channel simulator is constructed by incorporating the spatial-temporal properties as well as the time-varying nature of propagation environments. A two-state semi-Markov model is used to account for the births and deaths of scattering clusters, which represents an improvement over the conventional Markov model where the duration in each state is forced to follow an exponential distribution. The spatial-temporal variations of clusters within their lifespan are modeled based on the real-life measurement results. The ranges of angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) for each cluster are partitioned into finite number of intervals using the deterministic simulation methods. Subsequently, the cluster properties at different intervals can be derived from the empirical findings in previous channel-measurement campaigns. The efficacy of the proposed simulator is demonstrated by applying it to characterize a time-varying multiple-input multiple-output (MIMO) channel.

Architecture and its implementation for robots to navigate in unknown indoor environments

It is discussed with the design and implementation of an architecture for a mobile robot to navigate in dynamic and unknown indoor environments. The architecture is based on the framework of Open R ...

Person following and mobile robot via arm-posture driving using color and stereovision

This paper describes an approach to arm-posture recognizing and interpreting by mobile robot while following a person. We combine color and stereo cues to detect and track a person in dynamic indoor environments in real-time. The arm-postures are very simple and can be described by a spatial relation between a person's face and hands. Color image processing and labeling techniques are used to detect candidates of face, hands and shirt. The localization and recognition take place by analyzing the labeled images and utilizing a range histogram. Using heuristics for the size and spatial relations we can locate the tracked person as well as the person's face and hands. Experiments conducted with a Pioneer 2 DX mobile robot equipped with an active color camera and a stereovision system have shown the presented approach to be repeatable and robust to noise.

Real time behavior-based control on a mobile robot

This paper discusses and compares some common architectures used in autonomous mobile robotics. Then it describes a behavior-based autonomous mobile robot that was implemented successfully in the Robotics Lab of the Department of Precision Mechanical Engineering. Fuzzy controller was used to implement the emergency behavior, the behaviors arbitration was implemented using the subsumption architecture. In an unknown dynamic indoor environment, the robot achieved real-time obstacle avoidance properties that are cruel for mobile robotics.

Spatio-temporal correlation properties for the 5.2 GHz indoor propagation environments

The spatial and temporal correlation properties of a wideband dynamic directional indoor channel at 5.2 GHz are presented based on extensive measurement campaigns in four different environments under various propagation scenarios. Channel spatio-temporal dispersions are assessed in terms of the root mean square (RMS) delay spread and RMS azimuth spread, respectively. A strong correlation is observed with the presence of a line-of-sight (LOS) path, but degraded when the LOS is obstructed. The variations of the spatio-temporal dispersions with mobility are also investigated, where higher values of spatio-temporal dispersions were found when the transmitter and receiver separation increased, particularly in a more cluttered environment.

CONCURRENT MAP BUILDING AND LOCALIZATION ON INDOOR DYNAMIC ENVIRONMENTS

A system that builds and maintains a dynamic map for a mobile robot is presented. A learning rule associated to each observed landmark is used to compute its robustness. The position of the robot during map construction is estimated by combining sensor readings, motion commands, and the current map state by means of an Extended Kalman Filter. The combination of landmark strength validation and Kalman filtering for map updating and robot position estimation allows for robust learning of moderately dynamic indoor environments.

A state space model for predicting and controlling the temperature responses of indoor air zones

Indoor temperature distributions and air flows lead to the variation of local thermal comfort from place to place. To have more precise predictions and better control of the thermal conditions in the working zone where the room occupant sits and works, a both detailed and fast model of the dynamic indoor temperature distributions is needed. Unfortunately, very few papers studied such models due to the complexity of fluid (air) flows. This paper discusses a zonal model which is derived from computational fluid dynamics (CFD) and the output of a CFD code. The model is validated with experimental results. In order to design better control systems, the zonal model is transformed into a state space representation form. One example is given on how the state space model can be used for temperature predictions and more precise temperature controls.