Human-Robot Localization Using Wireless Pyroelectric Infrared and Multi-Sensor Fusion Approaches

• Main Authors: Chien Chung Chen, 陳建仲
• Other Authors: 羅仁權
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/44405908094515873962

博士 === 國立中正大學 === 電機工程研究所 === 100 === 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, but these remain significant difficulties. For instance, the Pyroelectric Infrared (PIR) system provides less accurate information of human location and is restricted when there are multiple targets. Furthermore, the Radio Frequency (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 pyroelectric infrared (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 radio frequency signal localization system which utilize the received signal strength (RSS) propagation model. We have developed and experimentally demonstrated a WPIR sensory fusion system which can be successfully applied in localizing multiple targets. With an accurate localization mechanism for the indoor environment, the provision of appropriate services for people can be realized. 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 highly accurate localization mechanism by using ultrasonic (US), dead reckoning (DR), and radio frequency (RF) information which is processed through the particle filter algorithm. Mobile sensor node with accurate localization ability is of great interest to basic researches and applications, such as sensor deployment, coverage management, dynamic power management and etc. In this study 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 pre-deployed 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 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 trade-off 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.