Trung-Kien Dao

The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work

This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors’ estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described.

Speed-adaptive roll-angle-tracking control of an unmanned bicycle using fuzzy logic

This paper presents the development of dynamic equations and roll-angle-tracking controller of an unmanned bicycle. First, the equations of motion and constraints of a bicycle with rolling-without-slipping contact condition between wheels and ground are developed using Lagranges equations. The equations are then used to implement the simulation of the bicycle dynamics. With the bicycle model, a fuzzy-logic controller, which is adaptive to the speed change is implemented to control the bicycle to follow the roll-angle commands. The controller parameters where fuzzy membership functions are presented by scaling factors and deforming coefficients are optimised using genetic algorithms. Results show that the bicycle can follow the roll-angle command with short time delay and the control structure can adapt to a wide range of speed.

User Localization in Complex Environments by Multimodal Combination of GPS, WiFi, RFID, and Pedometer Technologies

Many user localization technologies and methods have been proposed for either indoor or outdoor environments. However, each technology has its own drawbacks. Recently, many researches and designs have been proposed to build a combination of multiple localization technologies system which can provide higher precision results and solve the limitation in each localization technology alone. In this paper, a conceptual design of a general localization platform using combination of multiple localization technologies is introduced. The combination is realized by dividing spaces into grid points. To demonstrate this platform, a system with GPS, RFID, WiFi, and pedometer technologies is established. Experiment results show that the accuracy and availability are improved in comparison with each technology individually.

A compensated yaw-moment-based vehicle stability controller

This paper describes an Electronic Stability Program (ESP) controller acting on the braking system to generate a corrective yaw moment that helps a vehicle to follow the desired course from the driver. The approach is based on the estimation of the desired yaw rate and the sideslip angle. Model-free Fuzzy-Logic Controllers optimised by Genetic Algorithms are used to control the vehicle tracking the desired yaw rate while keeping the sideslip angle small. A hydraulic-pressure model is developed for the Electro-Hydraulic Brake system for simulation. The performance of the control system for various emergency driving situations is verified by simulations.

Sliding-mode control for the roll-angle tracking of an unmanned bicycle

This study investigates the roll-angle tracking control of an unmanned bicycle using a sliding-mode controller (SMC). The roll angle is controlled at a specific speed via a simple proportional, derivative (PD) controller to generate input–output data including steering torque as well as roll and steering angles. The collected data are then used to identify a one-input two-output linear model by a prediction-error identification method using parameterisation in a canonical state-space form derived as a Whipple model. Once the linear model is obtained, the SMC can be designed to control the bicycle. Simulations and comparisons with a proportional, integral, derivative (PID) controller show that this SMC is robust against changes and variations in speed as well as external disturbances.

A Robust WLAN Positioning System Based on Probabilistic Propagation Model

User localization is the key to enable many location-based services. Localization techniques have been actively studied recently due to service as well as safety and security matters. There are many localization systems with different architectures, configurations, accuracies and reliabilities. However, no technique is now generally applicable for indoor environments. In this paper, a probabilistic propagation model of WiFi signals in an environment with walls/floors, and its application to a localization technique using WiFi signal strength, are introduced. A small program installed on the smart device regularly scans the signal strengths to surrounding WiFi access points and send information to a central server to calculate the position. The user location is achieved in 3D space by a robust hybrid method which is based on the probabilistic propagation model and takes the advantages from both well-known geometrical-calculation and finger-printing approaches: low site-survey cost and robustness. The parameters are tuned by using a genetic algorithm from easily collected data.

Fully-automated person re-identification in multi-camera surveillance system with a robust kernel descriptor and effective shadow removal method

In this paper, a fully-automated person Re-ID (Re-identification) system is proposed for real scenarios of human tracking in non-overlapping camera network. The system includes two phases of human detection and Re-ID. The human ROIs (Regions of Interest) are extracted from human detection phase and then feature extraction is done on these ROIs in order to build human descriptor for Re-ID. Unlike other approaches which deal with manually-cropped human ROIs for person Re-ID, in this system, the person identity is determined based on the human ROIs extracted automatically by a combined method of human detection. Two main contributions are proposed on both phases of human detection and Re-ID in order to enhance the performance of person Re-ID system. First, an effective shadow removal method based on score fusion of density matching is proposed to get better human detection results. Second, a robust KDES (Kernel DEScriptor) is extracted from human ROI for person classification. Additionally, a new person Re-ID dataset is built in real surveillance scenarios from multiple cameras. The experiments on benchmark datasets and our own dataset show that the person Re-ID results using the proposed solutions outperform some of the state-of-the-art methods. Density-based score fusion scheme for shadow removal is proposed.An efficient KDES descriptor for person Re-ID in multi-camera networkFully-automated person Re-ID in multi-camera surveillance system

Multimodal Combination of GPS, WiFi, RFID and Step Count for User Localization

In this paper, a conceptual design of an indoor/outdoor localization system using combination of multiple localization technologies based on the idea of dividing spaces into grid points is presented. In implementation part, we have built the system with GPS, RFID, WiFi positioning and step count techniques, in which the system has been proven to improve accuracy and availability compared to each technology individually.

Path Tracking Control of a Motorcycle Based on System Identification

This study investigates the roll angle tracking and path tracking controls of a motorcycle. For the control design, a required linear model is obtained from the system identification method. The roll angle is controlled at a specific speed via a simple PID controller to generate input-output data, including steering torque, as well as roll and steering angles. The collected data are then used to identify a one-input two-output linear model by a prediction error identification method using parameterization in a canonical state-space form derived as a Whipple model. With the obtained linear model, full-state feedback (FSF) is designed for roll angle tracking control. Simulations and comparisons with a PID controller show that this FSF is robust against changes in speed as well as external disturbances. On the basis of the roll angle tracking controller, a path tracking controller by path preview is developed with consideration of disturbance rejection. The simulations show the effectiveness of the proposed control scheme.

A study of bicycle dynamics via system identification

This study investigates bicycle dynamic properties by using system identification approaches. The nonlinear bicycle model with configuration parameters from a previously developed benchmark model is studied. The roll angle of the bicycle is controlled at different speeds to generate input-output data including steering torque, roll and steering angles. The collected data are then used to identify the one-input two-output linear model by a prediction-error identification method using parameterization in canonical state-space form. Numerous properties for various speed ranges are discussed from the pole and zero locations of the identified linear model. The system stability, limit-cycle phase portraits of the roll and steering angles, and the non-minimum phase property of the nonlinear system are further investigated and compared.