Adaptive observer-based trajectory tracking control of nonholonomic mobile robots

In this paper, an adaptive observer-based trajectory tracking problem is solved for nonholonomic mobile robots with uncertainties. An adaptive observer is first developed to estimate the unmeasured velocities of a mobile robot with model uncertainties. Using the designed observer and the backstepping technique, a trajectory tracking controller is designed to generate the torque as an input. Using Lyapunov stability analysis, we prove that the closed-loop system is asymptotically stable with respect to the estimation errors and tracking errors. Finally, the simulation results are presented to validate the performance and robustness of the proposed control system against uncertainties.     

Reliability-based design optimization with confidence level under input model uncertainty due to limited test data

For obtaining a correct reliability-based optimum design, the input statistical model, which includes marginal and joint distributions of input random variables, needs to be accurately estimated. However, in most engineering applications, only limited data on input variables are available due to expensive testing costs. The input statistical model estimated from the insufficient data will be inaccurate, which leads to an unreliable optimum design. In this paper, reliability-based design optimization (RBDO) with the confidence level for input normal random variables is proposed to offset the inaccurate estimation of the input statistical model by using adjusted standard deviation and correlation coefficient that include the effect of inaccurate estimation of mean, standard deviation, and correlation coefficient.     

Localization using GPS and VISION aided INS with an image database and a network of a ground-based reference station in outdoor environments

GPS/INS integrated systems do not guarantee robustness and accuracy of localization, because GPS has vulnerability to external disturbances. However, the overall performance and reliability of the system can be significantly improved by fusing multiple sensors with a different operating principle. In outdoor environments where GPS may be blocked, there are many features compared to the open space and these features can provide much information for UGV localization. Thus, this paper proposes an improved localization algorithm based on the hierarchical federation of three measurement layers, i.e., GPS, INS, and visual localization, to overcome the shortcomings of GPS/INS integrated systems. The proposed algorithm automatically switches the operation modes according to GPS status and a network of a ground-based reference station. A vocabulary tree with SURF is used in the visual localization method. In the data fusion of visual localization and INS, an asynchronous and time-delayed data fusion algorithm is presented because visual localization is always time-delayed compared with INS. By using DGPS to obtain the reference position under the dynamic conditions of the reference station, the restrictions of the conventional DGPS are overcome and all UGVs within WiBro communication range of the reference station can accurately estimate the position with a common GPS. The experiment results with a predefined path demonstrate enhancement of the robustness and accuracy of localization in outdoor environments.     

Localization of an unmanned ground vehicle based on hybrid 3D registration of 360 degree range data and DSM

A computer vision technique to identify the location of an outdoor unmanned ground vehicle (UGV) is presented. The proposed technique is based on hybrid 3D registration of 360 degree laser range data to a digital surface model (DSM). Range frames obtained from 48 laser detectors are aligned with the reference coordinate system of the DSM. Three novel approaches are proposed for accurate and fast 3D registration of range data and the DSM. First, a two-step hybrid 3D registration technique is proposed. A pair-wise registration step of two consecutive range frames is followed by a refinement step using a layered DSM. Second, a fast projection-based pair-wise registration is proposed by employing rasterized 360 degree range frames. Third, a high elevation DSM is divided into several elevation layers and correspondence search is done near the vehicle’s current elevation. This reduces the number of matching outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on five outdoor paths is presented with respect to ground truth.     

A dynamic priority-based approach to concurrent toolpath planning for multi-material layered manufacturing

This paper presents an approach to concurrent toolpath planning for multi-material layered manufacturing (MMLM) to improve the fabrication efficiency of relatively complex prototypes. The approach is based on decoupled motion planning for multiple moving objects, in which the toolpaths of a set of tools are independently planned and then coordinated to deposit materials concurrently. Relative tool positions are monitored and potential tool collisions detected at a predefined rate. When a potential collision between a pair of tools is detected, a dynamic priority scheme is applied to assign motion priorities of tools. The traverse speeds of tools along the x-axis are compared, and a higher priority is assigned to the tool at a higher traverse speed. A tool with a higher priority continues to deposit material along its original path, while the one with a lower priority gives way by pausing at a suitable point until the potential collision is eliminated. Moreover, the deposition speeds of tools can be adjusted to suit different material properties and fabrication requirements. The proposed approach has been incorporated in a multi-material virtual prototyping (MMVP) system. Digital fabrication of prototypes shows that it can substantially shorten the fabrication time of relatively complex multi-material objects. The approach can be adapted for process control of MMLM when appropriate hardware becomes available. It is expected to benefit various applications, such as advanced product manufacturing and biomedical fabrication.     

Study of polymer‐network structure on polymer‐stabilized blue phase

Abstract— To understand the mechanism of the disclination defect of the liquid‐crystal (LC) phase, this study was conducted to directly analyze the polymer‐network (PN) structure of polymer‐stabilized blue phase (PSBP), which is minutely formed on all LC layers. The PN was examined after first removing the glass decap and then the LC. Important to note is that the removal of the glass decap did not affect or damage the PN structure. The PN was determined to be a stable structure without any change to the thickness of the layer. When removing the LC, both hexane and acetone solutions were used. Moreover, there was no structural deformation to the PN when using the hexane solution. The results of the study show that the actual size of the polymer chain is in fact 50–60 nm, five times larger than previous theories which estimated the size to be only 10 nm. In addition, this study confirmed that the pores between the PN are 100–200 nm. The PN structure was shown to be susceptible to change based on different heating temperatures. In summation, now that defect lines of a LC display (LCD) could be directly measured, further progress and development in the theoretical interpretations of the Kerr effect on PSBP can be realized.     

Knowledge search and people with high epistemic curiosity

Porter sites have tried to increase their business potentials by helping users easily engage in diverse online activities such as search, entertainment, online communities, and others. Knowledge search engine is one of the most successful killer applications increasing user loyalty. However, most studies have independently focused on search engine technology such as search keyword algorithm, presentation of information and user characteristics such as cognitive style, search experiences, and skill levels. However, these previous studies lack an integrated understanding of causal links among critical factors predicting user motives and intention involving more situation-specific user characteristics. To fill these gaps in the literature, the present study focuses on whether knowledge characteristics such as specialization, preciseness, and diversity, and system characteristics such as interactivity, responsiveness, and communication richness are important in forming user motives and intention. The present study also identifies a moderating role of epistemic curiosity in the links between motives and intention. Two hundred and fifty-five data from Korean university students confirmed that knowledge and services characteristics such as specialty, preciseness, diversity, communication richness improve user motives, which have a positive impact on intention. Epistemic curiosity has a moderating effect on the links between motives and intention. Theoretical and practical implications are discussed in conclusion.     

Trajectory generation and control for a biped robot walking upstairs

This paper presents an effective and systematic trajectory generation method, together with a control method for enabling a biped robot to walk upstairs. The COG (center of gravity) trajectory is generated by the VHIPM (virtual height inverted pendulum mode) for the horizontal motion and by a 6th order polynomial for the vertical motion; an ankle compliance control (ACC) is also added into the robot control. The proposed methods are evaluated by simulations as well as being implemented in a robot for the performance verification. The results show that the proposed methods can generate stable motions when walking upstairs, and these can significantly reduce the zero moment point (ZMP) errors compared with other methods, enabling the robot to walk up steeper stairs.     

Pattern recognition using feature feedback: Application to face recognition

In this paper, we propose a new pattern recognition method using feature feedback and present its application to face recognition. Conventional pattern recognition methods extract the features employed for classification using PCA, LDA and so on. On the other hand, in the proposed method, the extracted features are analyzed in the original space using feature feedback. Using reverse mapping from the extracted features to the original space, we can identify the important part of the original data that affects the classification. In this way, we can modify the data to obtain a higher classification rate, make it more compact or abbreviate the required sensors. To verify the applicability of the proposed method, we apply it to face recognition using the Yale Face Database. Each face image is divided into two parts, the important part and unimportant part, using feature feedback, and the classification performed using the feature mask obtained from feature feedback. Also, we combine face recognition with image compression. The experimental results show that the proposed method works well.     

Mobile robot localization with gyroscope and constrained Kalman filter

The odometry information used in mobile robot localization can contain a significant number of errors when robot experiences slippage. To offset the presence of these errors, the use of a low-cost gyroscope in conjunction with Kalman filtering methods has been considered by many researchers. However, results from conventional Kalman filtering methods that use a gyroscope with odometry can unfeasible because the parameters are estimated regardless of the physical constraints of the robot. In this paper, a novel constrained Kalman filtering method is proposed that estimates the parameters under the physical constraints using a general constrained optimization technique. The state observability is improved by additional state variables and the accuracy is also improved through the use of a nonapproximated Kalman filter design. Experimental results show that the proposed method effectively offsets the localization error while yielding feasible parameter estimation.