Wi-Fi-based localization using received signal strength (RSS) with pedestrian dead reckoning (PDR) algorithm is widely used to track pedestrians in indoor environments. However, the unsatisfactory ...deployment of Wi-Fi access points (APs) in buildings and the unstable performance of PDR are still key problems that lead to low localization accuracy. In this paper, we make contributions on proposing a hybrid Wi-Fi and Bluetooth Low Energy (BLE) indoor localization system (ILS) based on an efficient BLE deployment strategy and hierarchical topological fingerprinting (HTF). For the BLE deployment strategy, we deploy BLE beacons in places that do not have clear Wi-Fi signals for localization. This efficiently increases the localization accuracy. For HTF, we hierarchically localize targets based on a topological fingerprint (TF) map. First of all, we quickly localize the room in which the target is located by Dendogram-based support vector machine (DSVM). Then, the specific position of the target is estimated by fusing Wi-Fi and BLE signals with the TF map. The new BLE-based fingerprinting algorithm is used to localize targets in environments sparsely populated by BLE beacons. We conduct physical experiments in a real building. The experimental results demonstrate that the beacons deployed based on our proposed deployment strategy results in greater localization accuracy. Furthermore, the HTF approach performs better than the other commonly used localization methods.
Indoor localization based on received signal strength (RSS) will result in a decreased precision after the environment changes. In this paper, we develop an adaptive wireless indoor localization ...system (ILS) for dynamic environments. The system consists of the following two components: an automated database updating process and a new fingerprinting algorithm called adaptive signal model fingerprinting (ASMF). In the ILS, a self-locating mobile robot is set up to continuously collect RSS measurement data within the localization space for autonomously updating the fingerprint database. ASMF is designed to reduce the time consumption and the amount of RSS data needed for updating the database. The fingerprint of the signal in ASMF is constructed by the position of the beacons and three signal models, which can be duly corrected based on the regression and optimization algorithm. Finally, we propose experiments for positioning targets in the static and dynamic environments and compare the results of the ASMF algorithm with traditional trilateration and k-nearest-neighbor fingerprinting algorithms. The experimental results demonstrate that the ASMF-based ILS provides much better performance in both static and dynamic environments; furthermore, the positioning accuracy can be actually maintained by the autonomous updated ASMF database.
Mobile sensor node deployment and power management are important issues in the wireless sensor network system. This study designs a mobile sensor node platform to achieve a highly accurate ...localization mechanism by using ultrasonic, dead reckoning, and radio frequency information which is processed through a particle filter algorithm. Mobile sensor node with accurate localization ability is of great interest to basic research works and applications, such as sensor deployment, coverage management, dynamic power management, etc. In this paper, we propose an efficient mobile sensor node deployment method, grid deployment, where the map is divided into multiple individual grids and the weight of each grid is determined by environmental factors such as predeployed nodes, boundaries, and obstacles. The grid with minimum values is the goal of the mobile node. We also design an asynchronous power management strategy in our sensor node to reduce power consumption of the sensor network. Several factors such as probability of event generation, battery status, coverage issues, and communication situations have also been taken into consideration. In network communication, we propose an asynchronous awakening scheme so that each node is free to switch on or off its components according to observed event statistics and make a tradeoff between communication and power consumption. The deepest sleep state period is determined by the residual power. By combining these methods, the power consumption of the sensor node can be reduced.
The objective of this paper is to have an intelligent service robot that not only autonomously estimates the environment structure but also simultaneously detects the commonly recognized ...symbols/signs in the building. The result is an information-enriched map constructed by the environment geometry from a laser ranger and the indoor indicators from visual image. To implement this enriched map, multisensor fusion techniques, i.e., covariance intersection and covariance union, are tactically utilized for robust pose association and sign estimation. Furthermore, an improved alignment technique is applied to promote the mapping precision in a single simultaneous localization and mapping process with the posterior convenience. Additionally, a 2.5-D environment enriched map has been rapidly constructed with the Mesa SwissRanger. We have successfully experimentally demonstrated the proof of concept and summarized it in the conclusion.
In this paper, a service-oriented multiagent system (SoMAS) for the control and analysis of the cyber-physical system (CPS) in manufacturing automation utilizing a noncontact dynamic obstacle ...avoidance seven-DoF robot arm is presented. The interfaces of the services which the robot arm subsystem should provide to fully exploit its capability are identified. Specifically, the services of moving, object recognition, object fetching, and safety of human-robot interaction are considered as the fundamental functionalities that the robot arm should provide. The way to evaluate the quality of services (QoS) for the robot arm subsystem is also explained. To build such a robot arm subsystem, the system architecture is proposed. Also, implementation for the subsystem which includes: 3-D model-based object recognition, grasp database for object fetching, and online noncontact obstacle avoidance for the safety of human-robot interaction is provided. The experimental results demonstrate that the capability of 3-D model-based object recognition, object fetching, and dynamic collision avoidance are successfully implemented.
Intelligent service robot development is an important and critical issue for human community applications. With the diverse and complex service needs, the perception and navigation are essential ...subjects. This investigation focuses on the synergistic fusion of multiple sensors for an intelligent service robot that not only performs self-localization and mapping but also detects moving objects or people in the building it services. First of all, a new augmented approach of graph-based optimal estimation was derived for concurrent robot postures and moving object trajectory estimate. Moreover, all the moving object detection issues of a robot's indoor navigation are divided and conquered via multisensor fusion methodologies. From bottom to up, the estimation fusion methods are tactically utilized to get a more precise result than the one from only the laser ranger or stereo vision. Furthermore, for solving the consistent association problem of moving objects, a covariance area intersection belief assignment is applied for motion state evaluation and the complementary evidences such as kinematics and vision features are both synergized together to enhance the association efficiency with the evidence fusion method. The proof of concept with experiments has been successfully demonstrated and analyzed.
An indoor localization and monitoring system for robots and people is an important issue in robotics research. Although several monitoring systems are currently under development by previous ...investigators, these issues remain significant difficulties. For instance, the pyroelectric IR (PIR) system provides less accurate information of human location and is restricted when there are multiple targets. Furthermore, the RF localization system is constrained by its limited accuracy. In this study, we propose an indoor localization and monitoring system based on a wireless and PIR (WPIR) sensory fusion system. We develop a sensor-network-based localization method called the WPIR inference algorithm. This algorithm determines the fused position from both the PIR localization system and RF signal localization system, which utilize the received signal strength propagation model. We have developed and experimentally demonstrated a WPIR sensory fusion system, which can be successfully applied in localizing multiple targets based on two robots and two people in this study. With an accurate localization mechanism for the indoor environment, the provision of appropriate services for people can be realized.
The objective of this paper is to review the theories and approaches of multisensor fusion and integration (MFI) with its application in mechatronics. MFI helps the system perceiving changes of the ...environment and monitoring the system itself. Since each individual sensor has its own inherent defects and limitations, MFI merges the redundant information acquired by multiple sensors synergistically to provide a more accurate perception and make an optimal decision in further. The wide application spectrum of MFI in mechatronics includes the industrial automation, the development of intelligent robots, military applications, biomedical applications, etc. In this paper, the architecture and algorithms of MFI are reviewed, and some implementation examples in industrial automation and robotic applications are presented. Furthermore, sensor fusion methods at different levels, namely, estimation methods, classification methods and inference methods, the most frequently used algorithms in previous researches with their advantages and limitations are summarized. Applications of MFI in robotics and mechatronics are discussed. Future perspectives of MFI deployment are included in the concluding remarks.
Indoor service robots accumulate errors when its own reference map differs from the true environment such as when furniture has been rearranged in an area. This results in poor localization accuracy ...when pose estimation relies on outdated maps. Traditional methods address this issue by rebuilding the reference map from scratch. In this article, we propose a histogram of oriented depth model (HODM) and its extraction approach using laser rangefinders and RGBD cameras. HODM aims to provide a light and robust localization module so that mobile robots work in environments required by rearrangement from time to time. The key concept of HODM is based on using histogram-based model matching for estimating indoor primary structures and floor layouts. HODM localization will use an HODM map as a reference in scan matching, and the experimental results show that the localization error is lower than traditional non-HODM-based localization methods. In the same indoor location, the mapping process is only required once. The HODM approach presented in this article shows two major contributions. First, the localization error is lower even with an outdated reference map when compared with traditional localization methods, and, second, the computational time of HODM is fast. We validate this proposed method through numerical simulations and actual experiments in our laboratory using our experimental mobile robot developed in our NTU-iCeiA robotics laboratory.
This article develops a high-stiffness, high-precision, hybrid tool center point (TCP) mode and a skew force free model-based (SFFMB) synchronous gantry-type design for a hybrid gantry-robot machine. ...For the new SFFMB synchronous gantry-type design, newly developed active/passive control models are presented to prevent gantry skew. The force ratio between the slave and master axes is generated, and experimental results show that the driving currents for the master/slave linear motor axes are lower when the SFFMB synchronous control function is enabled. This function makes the machine move smoothly even when deviations from squareness occur. These design approaches aim to improve the accuracy and performance at high speed to reduce the working cycle time for a machine with multiple degrees of freedom. This article makes three contributions to the literature. First, by considering the skew force issue, a new SFFMB synchronous gantry-type design is proposed to prevent gantry skew phenomenon. Second, to ensure exact omnidirectional linear movement, a novel hybrid TCP mode is proposed to decouple coordinate transformations into individual translation and rotation components. Third, based on the SFFMB synchronous control strategy and the hybrid TCP mode, we propose an effective calibration method to enhance the TCP accuracy. The new SFFMB synchronous gantry-type design and the accurate hybrid TCP mode are experimentally verified and demonstrated using a hybrid gantry-robot machine developed in our laboratory, which is based on our proposed synchronous control strategy.
