DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4/W5, 2015 Indoor-Outdoor Seamless Modelling, Mapping and Navigation, 21–22 May 2015, Tokyo, Japan DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS Y. C. Lai a, *, C. C. Chang b, C. M. Tsai b, S. Y. Lin c, S. C. Huang b a b Dept. of Aerospace and Systems Engineering, Feng Chia University, Taiwan - Microsystem Technology Center, Industrial Technology Research Institute, Taiwan - (jinja, scart)@itri.org.tw c Cloud Service Technology Center, Industrial Technology Research Institute, Taiwan - Commission WG IV/7 and WG V/4 KEY WORDS: Dead Reckoning, Fuzzy Logic, Multi-Sensor Fusion, Inertial Measure Unit, Wearable Device, Portable Device ABSTRACT: This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its usability. The experiment results of the proposed navigation system demonstrate good navigation performance in indoor environment with the accurate initial location and direction. 1. INTRODUCTION With the enormous progress in electronic and communication technologies, portable or wearable devices have become popular and affordable nowadays, and they have become widely used in various applications, such as sport monitoring and management, healthcare, visitor navigation, etc. The Global Navigation Satellite Systems (GNSS) such as Global Position System (GPS) can provide accurate location information in open outdoor spaces, but they are not always available especially in GPS-denied environments such as indoors, undergrounds, and urban environments (Hemin et al., 2015). To compensate the drawback of GNSS, some solutions, such as assisted GPS (A-GPS) and cellular-based positioning, but their accuracy is not enough to meet the demand of most indoor applications (Hui et al., 2007). Therefore, the development of indoor positioning systems, which are categorized into two types: device-free and device-based, has been a hot topic (Harle, 2013). Since the device-free type is still in its infancy and has a lot of limitations, the device-based becomes the main stream of indoor positioning (Youssef et al., 2007). Typical device-based location sensing methods include proximity(Hightower, 2004), triangulation (Harle, 2013), fingerprinting (Chintalapudi, et al., 2010), dead reckoning (Woodman and Harle, 2008), and so on. Due to the progress in low-cost sensors based on micro electromechanical system (MEMS), Pedestrian Dead Reckoning (PDR) systems are becoming feasible options for indoor navigation and tracking. Low-cost sensors mean lower performance and high noisy compared with the expensive sensors. Therefore, the integration and combination of different sensors and algorithms are required to enhance the accuracy and usability of the PDR with low-cost sensors. In this study, a sensor calibration procedure based on the scalar calibration and the least squares methods are induced in this study to improve the accuracy of the inertial sensors. With the calibrated inertial data, a PDR system based on multi-sensor fusion and fuzzy logic estimation algorithms is proposed. It is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wear able inertial measure unit (IMU) were developed. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the walking length of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is * Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-4-W5-81-2015 81 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4/W5, 2015 Indoor-Outdoor Seamless Modelling, Mapping and Navigation, 21–22 May 2015, Tokyo, Japan calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. 2. HARDWARE DEVELOPMENT AND INERTIAL SENSOR CALIBRATION 2.1 Wearable Inertial Sensor Module Development The sensors of the proposed pedestrian navigation system are low-cost accelerometer and gyroscope that measure the signals from the inertial motion of the target objective. They are also termed inertial sensors. These low-cost sensors based on MEMS technology are commonly found in various applications such as human body motion tracking and flight control of a consumer drone. The inertial sensors (...truncated)