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Based on laser-range-finder (LRF) sensing, the control design of location and orientation stabilization for the mobile robot is investigated. However, the practical limitation of the LRF sensing is usually ignored in the control design, which leads to incorrect localization and unexpected control results. The purpose of this study is to design the fuzzy controller subject to the practical limitation on the LRF-based localization for a differentially driven wheeled mobile robot.

First, the Takagi–Sugeno (T-S) fuzzy model is derived from the polar kinematic model of a differentially driven mobile robot. Then, the fuzzy controller is designed to the derived T-S fuzzy kinematic model in accordance with the Lyapunov stabilization theorem. The derived Lyapunov stabilization conditions for the fuzzy control design are expressed as the linear matrix inequality (LMI) form and effectively solved by LMI tools. The practical limitation on the LRF-based localization is also expressed as the LMI form and simultaneously solved with the control design.

The location and posture stabilization experiments are carried out on a mobile robot with LRF-based localization to prove the effectiveness of the proposed T-S fuzzy model-based control design. Furthermore, the ground truth experiment evaluates the accuracy of LRF-based localization.

The contribution of this study is to develop the fuzzy control law for a differentially driven wheeled mobile robot under the practical limitation on LRF-based localization. The proposed control design can be applied to other robots with practical limitations on the sensors.

This paper aims to improve the efficiency and the quality of metal dental prostheses, reporting on the first patient‐fitted titanium (Ti) complete denture base plate fabricated by integrating the technologies of computer‐aided design and computer‐aided manufacture (CAD/CAM) and laser rapid forming (LRF).

To make a complete Ti denture base plate, the traditional lost‐wax‐casting technique is commonly used in dentistry. In order to simplify this labor‐intensive process, a new method combined with LRF was invented. Initially, a maxillary edentulous plaster cast was converted to point cloud data by laser scanning system. Subsequently, point cloud data were reconstructed into a 3D solid digital cast, which is stored in standard triangulation language format. Thereafter the 3D denture base was sliced electronically into a sequence of layers defining the regions of the component and, based on it, the complete Ti denture base plate was built layer‐by‐layer using a laser additive manufacturing technology.

After CAD/CAM/LRF process, the Ti denture base plate was designed and successfully fabricated layer‐by‐layer. After the traditional dental finishing techniques, the complete Ti denture base plate was made and assessed by clinician and patient. The clinical evaluation on quality of fit was judged to be acceptable.

The CAD/CAM/LRF system is a potential candidate to replace the traditional lost‐wax‐casting technique and provides a new platform for the design and manufacturing of custom‐made Ti denture plates and other restorations especially for implant substructure and framework of partial removal of denture.

The purpose of this study is to develop a cost-effective autonomous wheelchair robot navigation method that assists the aging population.

Navigation in outdoor environments is still a challenging task for an autonomous mobile robot because of the highly unstructured and different characteristics of outdoor environments. This study examines a complete vision guided real-time approach for robot navigation in urban roads based on drivable road area detection by using deep learning. During navigation, the camera takes a snapshot of the road, and the captured image is then converted into an illuminant invariant image. Subsequently, a deep belief neural network considers this image as an input. It extracts additional discriminative abstract features by using general purpose learning procedure for detection. During obstacle avoidance, the robot measures the distance from the obstacle position by using estimated parameters of the calibrated camera, and it performs navigation by avoiding obstacles.

The developed method is implemented on a wheelchair robot, and it is verified by navigating the wheelchair robot on different types of urban curve roads. Navigation in real environments indicates that the wheelchair robot can move safely from one place to another. The navigation performance of the developed method and a comparison with laser range finder (LRF)-based methods were demonstrated through experiments.

This study develops a cost-effective navigation method by using a single camera. Additionally, it utilizes the advantages of deep learning techniques for robust classification of the drivable road area. It performs better in terms of navigation when compared to LRF-based methods in LRF-denied environments.

2D laser rangefinders (LRFs) are commonly used sensors in the field of robotics, as they provide accurate range measurements with high angular resolution. These sensors can be coupled with mechanical units which, by granting an additional degree of freedom to the movement of the LRF, enable the 3D perception of a scene. To be successful, this reconstruction procedure requires to evaluate with high accuracy the extrinsic transformation between the LRF and the motorized system.

In this work, a calibration procedure is proposed to evaluate this transformation. The method does not require a predefined marker (commonly used despite its numerous disadvantages), as it uses planar features in the point acquired clouds.

Qualitative inspections show that the proposed method reduces artifacts significantly, which typically appear in point clouds because of inaccurate calibrations. Furthermore, quantitative results and comparisons with a high-resolution 3D scanner demonstrate that the calibrated point cloud represents the geometries present in the scene with much higher accuracy than with the un-calibrated point cloud.

The last key point of this work is the comparison of two laser scanners: the lemonbot (authors’) and a commercial FARO scanner. Despite being almost ten times cheaper, the laser scanner was able to achieve similar results in terms of geometric accuracy.

This work describes a novel calibration technique that is easy to implement and is able to achieve accurate results. One of its key features is the use of planes to calibrate the extrinsic transformation.

The purpose of this paper is to propose a localizability-based particle filtering localization algorithm for mobile robots to maintain localization accuracy in the high-occluded and dynamic environments with moving people.

First, the localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Second, based on the classical two-sensor track fusion algorithm, the odometer-based proposal distribution function (PDF) is corrected, taking account of the localizability. Then, the corrected PDF is introduced into the classical PF with “roulette” re-sampling. Finally, the robot pose is estimated according to all the particles.

The experimental results show that, first, it is necessary to consider the influence of the prior-map during the localization in the high-occluded and dynamic environments. Second, the proposed algorithm can maintain an accurate and robust robot pose in the high-occluded and dynamic environments. Third, its real timing is acceptable.

When the odometer error and occlusion caused by the dynamic obstacles are both serious, the proposed algorithm also has a probability evolving into the kidnap problem. But fortunately, such serious situations are not common in practice.

To check the ability of real application, we have implemented the proposed algorithm in the campus cafeteria and metro station using an intelligent wheelchair. To better help the elderly and disabled people during their daily lives, the proposed algorithm will be tested in a social welfare home in the future.

The localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Based on the localizability, the odometer-based PDF is corrected properly.

The purpose of this paper is to model how geometric errors of a machined surface (or manufacturing errors) are related to locators’ error, workpiece form error and machine tool volumetric error. A kinematic model is presented that puts into relationship the locator error, the workpiece form deviations and the machine tool volumetric error.

The paper presents a general and systematic approach for geometric error modelling in drilling because of the geometric errors of locators positioning, of workpiece datum surface and of machine tool. The model can be implemented in four steps: (1) calculation of the deviation in the workpiece reference frame because of deviations of locator positions; (2) evaluation of the deviation in the workpiece reference frame owing to form deviations in the datum surfaces of the workpiece; (3) formulation of the volumetric error of the machine tool; and (4) combination of those three models.

The advantage of this approach lies in that it enables the source errors affecting the drilling accuracy to be explicitly separated, thereby providing designers and/or field engineers with an informative guideline for accuracy improvement through suitable measures, i.e. component tolerancing in design, machining and so on. Two typical drilling operations are taken as examples to illustrate the generality and effectiveness of this approach.

Some source errors, such as the dynamic behaviour of the machine tool, are not taken into consideration, which will be modelled in practical applications.

The proposed kinematic model may be set by means of experimental tests, concerning the industrial specific application, to identify the values of the model parameters, such as standard deviation of the machine tool axes positioning and rotational errors. Then, it may be easily used to foresee the location deviation of a single or a pattern of holes.

The approaches present in the literature aim to model only one or at most two sources of machining error, such as fixturing, machine tool or workpiece datum. This paper goes beyond the state of the art because it considers the locator errors together with the form deviation on the datum surface into contact with the locators and, then, the volumetric error of the machine tool.

In order to succeed in landing asteroids, good accuracy autonomous navigation is absolutely necessary. Aims to describe a new autonomous navigation algorithm.

First, gray images of asteroid surface are acquired by optical navigation camera, and nature feature points are detected and tracked autonomously. Second, the directional vector from spacecraft to the center of each feature point can be computed from the image coordinates in camera focal plane. Then, LIDAR/LRF is directed to three feature points and the distances from spacecraft to feature points are obtained. Last, the relative position vector from spacecraft to the target asteroid is reconstructed base on measurement outputs of navigation cameras and laser light radar (laser range finder).

Suppose the initial conditions presented in this paper, the autonomous optical navigation position error and velocity error are less than 1 m and 0.1 m/s, respectively; this navigation accuracy can satisfy the requirement of soft landing on asteroids.

Based on feature detection and tracking, an autonomous optical navigation scheme is brought out and the validity is confirmed by computer simulation.

Robot localization technology has been widely studied for decades and a lot of remarkable approaches have been developed. However, in practice, this technology has hardly been applied to common day-to-day deployment scenarios. The purpose of this paper is to present a novel approach that focuses on improving the localization robustness in complicated environment.

The localization robustness is improved by dynamically switching the localization components (such as the environmental camera, the laser range finder and the depth camera). As the components are highly heterogeneous, they are developed under the robotic technology component (RTC) framework. This simplifies the developing process by increasing the potential for reusability and future expansion. To realize this switching, the localization reliability for each component is modeled, and a configuration method for dynamically selecting dependable components at run-time is presented.

The experimental results show that this approach significantly decreases robot lost situation in the complicated environment. The robustness is further enhanced through the cooperation of heterogeneous localization components.

A multi-component automatic switching approach for robot localization system is developed and described in this paper. The reliability of this system is proved to be a substantial improvement over single-component localization techniques.

The purpose of this paper is to critically assess the theoretical underpinnings and extant progress of the research on regional multi-national enterprises (MNEs) and offer a blueprint for future research by re-conceptualizing how (regional) boundaries relate to the international diversification of MNEs.

The paper integrates key insights from the theory of the regional MNE and economic geography to re-orient the treatment of regional borders within international business (IB) literature.

The paper suggests that the (L) component within the ownership location and internalization (OLI) paradigm should be disaggregated into continuous “distance effects” and discrete “border effects”. Within this rubric, regional borders represent discrete border effects that generate discontinuities that are permeable, fluid and firm specific. Such reconceptualization opens up avenues for future research and more tightly integrates the research on regional MNEs with other research streams.

IB scholars need to make concerted effort to think of regions as one among several parameters in studying the strategy and structure of MNEs. A stronger focus on internal processes and mechanisms elucidating the main drivers of MNEs strategies is needed.

The paper offers innovative ways in which future research can advance the study of how regions matter in the internationalization strategy of MNEs.