• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.10
• /
• pp.1044-1050
• /
• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.11
• /
• pp.1034-1037
• /
• 2015

In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.3
• /
• pp.243-250
• /
• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• Journal of Mechanical Science and Technology
• /
• v.19 no.6
• /
• pp.1253-1267
• /
• 2005

Misalignment can be an important problem in the integration of GPS/INS. Observability analysis of the alignment errors in the integration of low-grade inertial sensors and multi-antenna GPS is presented in this paper. A control-theoretic approach is adopted to study the observability of time-varying error dynamics models. The relationship between vehicle motions and the observability of the errors in the lever arm and relative attitude between GPS antenna array and IMU is given. It is shown that alignment errors can be made observable through maneuvering. The change of acceleration makes the components of the relative attitude error that are orthogonal to the direction of the acceleration change observable. The change of angular velocity makes the components of the lever arm error that are orthogonal to the direction of the angular velocity observable. The motion of constant angular velocity has no influence on the estimation of the lever arm.

• Korean Journal of Applied Biomechanics
• /
• v.29 no.1
• /
• pp.1-8
• /
• 2019

Objective: The purpose of this study was to confirm that the cross-country ski sprint course in PyeongChang, where the 2018 Winter Olympics course was to utilize wearable devices equipped with inertial measurement unit (IMU), global positioning system (GPS) and heart rates sensor. Method: For the data collection, two national level cross-country (XC) skiers performed classic technique on the entire sprint course. We analyzed cycle characteristics, range of motion on double poling (DP) technique, average velocity, and displacement of 3 points according to the terrain. Results: The absolute cycle time gradually decreased during starting, middle and finish sections. While the length of the DP increased and the heart rates tended to increase for men skier. In addition, the results indicated that range of motion of knee joint during starting and finish section decreased more than middle section. The errors of latitude and longitude data collected through GPS were within 3 m from 3 points. Conclusion: Through the first case study in Korea, which analyzed the location and condition of XC skiers in the entire sprint course in real time, confirmed that feedback was available in the field using various wearable sensors.

• Journal of Positioning, Navigation, and Timing
• /
• v.8 no.2
• /
• pp.49-58
• /
• 2019

A number of techniques have been studied to estimate the position of pedestrians in indoor space. Among them, the technique of estimating the position using only the sensors attached to the body of the pedestrian without using the infrastructure is regarded as a very important technology for special purpose pedestrians such as the firefighters. In particular, it forms a research field under the name of Pedestrian Dead Reckoning (PDR). In this paper, we focus on a method for step detection which is essential when performing PDR using Inertial Measurement Unit (IMU) mounted on a shoe. Many researches have been done to detect the stance phase where the foot contacts the ground. Most of these methods, however, have a way to detect the specific size of the sensor signal and require thresholds for these methods. This has the difficulty of changing these thresholds if the user is different. To solve this problem, we propose a stance phase detection method that does not require any threshold value. It is expected that this result will make it easier to commercialize the technology because PDR can be implemented without user-dependent parameter setting.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.5
• /
• pp.289-295
• /
• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• Journal of Positioning, Navigation, and Timing
• /
• v.10 no.3
• /
• pp.189-196
• /
• 2021

In this paper, we propose techniques to correct the altitude error and heading error of 3D Pedestrian Inertial Navigation (PIN). When a PIN is used to estimate the location of a pedestrian only with an Inetrial Measurement Unit (IMU) without infrastructure, there is a problem in that the location error gradually increases due to the limitation of the observability of the filter. To solve this problem without additional sensors, we propose two techniques in this paper. First, stair walking is recognized in consideration of the altitude difference that may occur during one step. If it is recognized as stair walking, only Zero-velocity UPdaTe (ZUPT) is performed, and if it is recognized as level walking, ZUPT + Altitude Damping (AD) is performed together to correct the altitude error. Second, the straight-line movement direction is calculated through the difference of the estimated position, and the heading error is corrected by matching this information with the link information of the digital map. By applying these techniques, it is verified through real tests that accurate three-dimensional location information of pedestrians can be estimated without infrastructure.

• Journal of Korea Multimedia Society
• /
• v.24 no.3
• /
• pp.355-372
• /
• 2021

Recently, high-performance HMDs (Head-Mounted Display) are becoming wireless due to the growth of virtual reality technology. Accordingly, environmental constraints on the hardware usage are reduced, enabling multiple users to experience virtual reality within a single space simultaneously. Existing multi-user virtual reality platforms use the user's location tracking and motion sensing technology based on vision sensors and active markers. However, there is a decrease in immersion due to the problem of overlapping markers or frequent matching errors due to the reflected light. Goal of this study is to develop a multi-user virtual reality moving platform in a single space that can resolve sensing errors and user immersion decrease. In order to achieve this goal hybrid sensing technology was developed, which is the convergence of vision sensor technology for position tracking, IMU (Inertial Measurement Unit) sensor motion capture technology and gesture recognition technology based on smart gloves. In addition, integrated safety operation system was developed which does not decrease the immersion but ensures the safety of the users and supports multimodal feedback. A 6 m×6 m×2.4 m test bed was configured to verify the effectiveness of the multi-user virtual reality moving platform for four users.

• The Journal of Korea Robotics Society
• /
• v.16 no.4
• /
• pp.291-298
• /
• 2021

In this study, we present a multi-sensor module for snake robot searching survivors in a narrow space. To this end, we integrated five sensor systems by considering the opinions of the first responders: a gas sensor to detect CO₂ gases from the exhalation of survivors, a CMOS camera to provide the image of survivors, an IR camera to see in the dark & smoky environment, two microphones to detect the voice of survivors, and an IMU to recognize the approximate location and direction of the robot and survivors. Furthermore, we integrated a speaker into the sensor module system to provide a communication channel between the first responders and survivors. To integrated all these mechatronics systems in a small, compact snake head, we optimized the positions of the sensors and designed a stacked structure for the whole system. We also developed a user-friendly GUI to show the information from the proposed sensor systems visually. Experimental results verified the searching function of the proposed sensor module system.