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Special Issue "Smart Sensors for Mechatronic and Robotic Systems"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 January 2018).

Special Issue Editors

Prof. Dr. Subhas Mukhopadhyay
E-Mail Website
Guest Editor
School of Engineering, Macquarie University, Australia
Interests: sensors and sensing technology; wirless sensor networks; instrumentation; Internet of Things (IoT); mechatronics and robotics
Special Issues and Collections in MDPI journals
Dr. Mohsen Asadnia
E-Mail Website
Guest Editor
School of Engineering, Macquarie University, NSW 2109, Australia
Interests: MEMS/NEMS; sensory systems; bioinspired sensors; chemical sensors; auditory system
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Smart sensors and sensing technology plays an important role towards the development of high performance mechatronics, robotics and autonomous system. This Special Issue aims to publish original, significant and visionary papers describing scientific methods and technologies that improve efficiency, productivity, quality and reliability in all areas of mechatronics, robotics and autonomous system. This Special Issue will provide a broad platform for publishing the many rapid advances that have been achieved to date in the area of mechatronics, robotics and autonomous system. In this Special Issue, we would like to focus on understanding what should be done to improve the perforemance of mechatronics, robotics and autonomous system. Submissions of scientific results from experts in academia and industry worldwide are strongly encouraged.

Prof. Dr. Subhas Mukhopadhyay
Dr. Mohsen Asadnia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart sensors
  • mechatronics
  • robotics
  • autonomous system
  • MEMS & NEMS sensors
  • Biomimetic sensors, wireless sensor networks
  • Internet of Things
  • IoT Based mechatronics systems
  • wireless mechatronics

Published Papers (19 papers)

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Research

Open AccessArticle
Heading Estimation of Robot Combine Harvesters during Turning Maneuveres
Sensors 2018, 18(5), 1390; https://doi.org/10.3390/s18051390 - 01 May 2018
Abstract
Absolute heading is an important parameter for a robot combine harvester or a robot tracked combine harvester, especially while it is turning, but due to the rapid turning of robot combine harvesters, its inertial measurement unit gives a gyro measurement bias that causes [...] Read more.
Absolute heading is an important parameter for a robot combine harvester or a robot tracked combine harvester, especially while it is turning, but due to the rapid turning of robot combine harvesters, its inertial measurement unit gives a gyro measurement bias that causes heading drift. Our research goal is to estimate the absolute heading of robot combine harvesters by compensating this gyro measurement bias during non-linear turning maneuvers. A sensor fusion method like the extended Kalman filter combined with the tracked combine harvester dynamic model and sensor measurements was used to estimate the absolute heading of a robot combine harvester. Circular, sinusoidal and concave shapes were used to evaluate the estimated heading produced by the sensor fusion method. The results indicate that the estimated heading is better than measured heading which was calculated from the integration of yaw rate gyro measurements, and the root mean square errors (RMSEs) for estimated headings are smaller than the measured headings. In practics, the target of this paper is thus the estimation of a heading or absolute heading that is bias compensated, and can be further used to calculate the exact crop periphery for automatic path planning of robot combine harvesters. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Evaluating Muscle Activation Models for Elbow Motion Estimation
Sensors 2018, 18(4), 1004; https://doi.org/10.3390/s18041004 - 28 Mar 2018
Cited by 3
Abstract
Adoption of wearable assistive technologies relies heavily on improvement of existing control system models. Knowing which models to use and how to improve them is difficult to determine due to the number of proposed solutions with relatively little broad comparisons. One type of [...] Read more.
Adoption of wearable assistive technologies relies heavily on improvement of existing control system models. Knowing which models to use and how to improve them is difficult to determine due to the number of proposed solutions with relatively little broad comparisons. One type of these models, muscle activation models, describes the nonlinear relationship between neural inputs and mechanical activation of the muscle. Many muscle activation models can be found in the literature, but no comparison is available to guide the community on limitations and improvements. In this research, an EMG-driven elbow motion model is developed for the purpose of evaluating muscle activation models. Seven muscle activation models are used in an optimization procedure to determine which model has the best performance. Root mean square errors in muscle torque estimation range from 1.67–2.19 Nm on average over varying input trajectories. The computational resource demand was also measured during the optimization procedure, as it is an important aspect for determining if a model is feasible for use in a particular wearable assistive device. This study provides insight into the ability of these models to estimate elbow motion and the trade-off between estimation accuracy and computational demand. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton
Sensors 2018, 18(3), 909; https://doi.org/10.3390/s18030909 - 19 Mar 2018
Cited by 6
Abstract
To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. [...] Read more.
To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Study of the Navigation Method for a Snake Robot Based on the Kinematics Model with MEMS IMU
Sensors 2018, 18(3), 879; https://doi.org/10.3390/s18030879 - 16 Mar 2018
Cited by 3
Abstract
A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation [...] Read more.
A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot’s motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot’s motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot’s navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Experimental Robot Model Adjustments Based on Force–Torque Sensor Information
Sensors 2018, 18(3), 836; https://doi.org/10.3390/s18030836 - 11 Mar 2018
Cited by 3
Abstract
The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems [...] Read more.
The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM) to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM), is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP). Thanks to the use of information from force–torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Virtual Sensors for Advanced Controllers in Rehabilitation Robotics
Sensors 2018, 18(3), 785; https://doi.org/10.3390/s18030785 - 05 Mar 2018
Cited by 4
Abstract
In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential part. Usually, however, this is a complex task that requires the use of accurate sensors which increase the cost and the [...] Read more.
In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential part. Usually, however, this is a complex task that requires the use of accurate sensors which increase the cost and the complexity of the robotic device. In this work, we address the development of virtual sensors that can be used as an alternative of actual force and motion sensors for the Universal Haptic Pantograph (UHP) rehabilitation robot for upper limbs training. These virtual sensors estimate the force and motion at the contact point where the patient interacts with the robot using the mathematical model of the robotic device and measurement through low cost position sensors. To demonstrate the performance of the proposed virtual sensors, they have been implemented in an advanced position/force controller of the UHP rehabilitation robot and experimentally evaluated. The experimental results reveal that the controller based on the virtual sensors has similar performance to the one using direct measurement (less than 0.005 m and 1.5 N difference in mean error). Hence, the developed virtual sensors to estimate interaction force and motion can be adopted to replace actual precise but normally high-priced sensors which are fundamental components for advanced control of rehabilitation robotic devices. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices
Sensors 2018, 18(2), 640; https://doi.org/10.3390/s18020640 - 21 Feb 2018
Cited by 8
Abstract
Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, [...] Read more.
Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framework should perform the identification of ADL without Internet connection, performing these tasks locally on the mobile device, taking in account the hardware and software limitations of these devices. The main purpose of this paper is to present a new approach for the creation of a framework for the recognition of ADL, analyzing the allowed sensors available in the mobile devices, and the existing methods available in the literature. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Structured Kernel Subspace Learning for Autonomous Robot Navigation
Sensors 2018, 18(2), 582; https://doi.org/10.3390/s18020582 - 14 Feb 2018
Cited by 2
Abstract
This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a [...] Read more.
This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm
Sensors 2018, 18(2), 571; https://doi.org/10.3390/s18020571 - 13 Feb 2018
Cited by 18
Abstract
In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human–Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among [...] Read more.
In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human–Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator’s obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots’ path planning. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
H∞ Robust Control of a Large-Piston MEMS Micromirror for Compact Fourier Transform Spectrometer Systems
Sensors 2018, 18(2), 508; https://doi.org/10.3390/s18020508 - 08 Feb 2018
Cited by 2
Abstract
Incorporating linear-scanning micro-electro-mechanical systems (MEMS) micromirrors into Fourier transform spectral acquisition systems can greatly reduce the size of the spectrometer equipment, making portable Fourier transform spectrometers (FTS) possible. How to minimize the tilting of the MEMS mirror plate during its large linear scan [...] Read more.
Incorporating linear-scanning micro-electro-mechanical systems (MEMS) micromirrors into Fourier transform spectral acquisition systems can greatly reduce the size of the spectrometer equipment, making portable Fourier transform spectrometers (FTS) possible. How to minimize the tilting of the MEMS mirror plate during its large linear scan is a major problem in this application. In this work, an FTS system has been constructed based on a biaxial MEMS micromirror with a large-piston displacement of 180 μm, and a biaxial H∞ robust controller is designed. Compared with open-loop control and proportional-integral-derivative (PID) closed-loop control, H∞ robust control has good stability and robustness. The experimental results show that the stable scanning displacement reaches 110.9 μm under the H∞ robust control, and the tilting angle of the MEMS mirror plate in that full scanning range falls within ±0.0014°. Without control, the FTS system cannot generate meaningful spectra. In contrast, the FTS yields a clean spectrum with a full width at half maximum (FWHM) spectral linewidth of 96 cm−1 under the H∞ robust control. Moreover, the FTS system can maintain good stability and robustness under various driving conditions. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments
Sensors 2018, 18(2), 438; https://doi.org/10.3390/s18020438 - 02 Feb 2018
Cited by 5
Abstract
A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split [...] Read more.
A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
A Novel Single-Axis MEMS Tilt Sensor with a High Sensitivity in the Measurement Range from 0 to 360
Sensors 2018, 18(2), 346; https://doi.org/10.3390/s18020346 - 25 Jan 2018
Cited by 2
Abstract
In this paper, a novel single-axis MEMS tilt sensor is presented. It contains a hexagonal proof mass, six micro-lever force amplifiers and three double-ended-tuning fork (DETF) resonant strain gauges. The proof mass is placed in the center with the micro-levers and the DETFs [...] Read more.
In this paper, a novel single-axis MEMS tilt sensor is presented. It contains a hexagonal proof mass, six micro-lever force amplifiers and three double-ended-tuning fork (DETF) resonant strain gauges. The proof mass is placed in the center with the micro-levers and the DETFs radially arrayed around. The variation of gravity acceleration applied on the proof mass will result in frequency shifts of the DETFs. Angular tilt can be got by analyzing the frequency outputs. The structural design of the tilt sensor is optimized by finite element simulation and the device is microfabricated using a silicon-on-insulator process, followed by open-loop and closed-loop characterizations. Results show that the scale factor of such sensor is at least 11.53 Hz/degree. Minimum Allan deviation of the DETF oscillator is 220 ppb (parts per billion) of the resonant frequency for an 5 s integration time. Resolution of the tilt sensor is 0.002 in the whole measurement range from 0 to 360 . Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
A Novel Event-Based Incipient Slip Detection Using Dynamic Active-Pixel Vision Sensor (DAVIS)
Sensors 2018, 18(2), 333; https://doi.org/10.3390/s18020333 - 24 Jan 2018
Cited by 3
Abstract
In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution [...] Read more.
In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Joint Bearing and Range Estimation of Multiple Objects from Time-Frequency Analysis
Sensors 2018, 18(1), 291; https://doi.org/10.3390/s18010291 - 19 Jan 2018
Cited by 1
Abstract
Direction-of-arrival (DOA) and range estimation is an important issue of sonar signal processing. In this paper, a novel approach using Hilbert-Huang transform (HHT) is proposed for joint bearing and range estimation of multiple targets based on a uniform linear array (ULA) of hydrophones. [...] Read more.
Direction-of-arrival (DOA) and range estimation is an important issue of sonar signal processing. In this paper, a novel approach using Hilbert-Huang transform (HHT) is proposed for joint bearing and range estimation of multiple targets based on a uniform linear array (ULA) of hydrophones. The structure of this ULA based on micro-electro-mechanical systems (MEMS) technology, and thus has attractive features of small size, high sensitivity and low cost, and is suitable for Autonomous Underwater Vehicle (AUV) operations. This proposed target localization method has the following advantages: only a single snapshot of data is needed and real-time processing is feasible. The proposed algorithm transforms a very complicated nonlinear estimation problem to a simple nearly linear one via time-frequency distribution (TFD) theory and is verified with HHT. Theoretical discussions of resolution issue are also provided to facilitate the design of a MEMS sensor with high sensitivity. Simulation results are shown to verify the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Development and Verification of a Novel Robot-Integrated Fringe Projection 3D Scanning System for Large-Scale Metrology
Sensors 2017, 17(12), 2886; https://doi.org/10.3390/s17122886 - 12 Dec 2017
Cited by 4
Abstract
Large-scale surfaces are prevalent in advanced manufacturing industries, and 3D profilometry of these surfaces plays a pivotal role for quality control. This paper proposes a novel and flexible large-scale 3D scanning system assembled by combining a robot, a binocular structured light scanner and [...] Read more.
Large-scale surfaces are prevalent in advanced manufacturing industries, and 3D profilometry of these surfaces plays a pivotal role for quality control. This paper proposes a novel and flexible large-scale 3D scanning system assembled by combining a robot, a binocular structured light scanner and a laser tracker. The measurement principle and system construction of the integrated system are introduced. A mathematical model is established for the global data fusion. Subsequently, a robust method is introduced for the establishment of the end coordinate system. As for hand-eye calibration, the calibration ball is observed by the scanner and the laser tracker simultaneously. With this data, the hand-eye relationship is solved, and then an algorithm is built to get the transformation matrix between the end coordinate system and the world coordinate system. A validation experiment is designed to verify the proposed algorithms. Firstly, a hand-eye calibration experiment is implemented and the computation of the transformation matrix is done. Then a car body rear is measured 22 times in order to verify the global data fusion algorithm. The 3D shape of the rear is reconstructed successfully. To evaluate the precision of the proposed method, a metric tool is built and the results are presented. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method
Sensors 2017, 17(12), 2742; https://doi.org/10.3390/s17122742 - 27 Nov 2017
Cited by 5
Abstract
In view of a dynamic obstacle environment with motion uncertainty, we present a dynamic collision avoidance method based on the collision risk assessment and improved velocity obstacle method. First, through the fusion optimization of forward-looking sonar data, the redundancy of the data is [...] Read more.
In view of a dynamic obstacle environment with motion uncertainty, we present a dynamic collision avoidance method based on the collision risk assessment and improved velocity obstacle method. First, through the fusion optimization of forward-looking sonar data, the redundancy of the data is reduced and the position, size and velocity information of the obstacles are obtained, which can provide an accurate decision-making basis for next-step collision avoidance. Second, according to minimum meeting time and the minimum distance between the obstacle and unmanned underwater vehicle (UUV), this paper establishes the collision risk assessment model, and screens key obstacles to avoid collision. Finally, the optimization objective function is established based on the improved velocity obstacle method, and a UUV motion characteristic is used to calculate the reachable velocity sets. The optimal collision speed of UUV is searched in velocity space. The corresponding heading and speed commands are calculated, and outputted to the motion control module. The above is the complete dynamic obstacle avoidance process. The simulation results show that the proposed method can obtain a better collision avoidance effect in the dynamic environment, and has good adaptability to the unknown dynamic environment. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy
Sensors 2017, 17(12), 2710; https://doi.org/10.3390/s17122710 - 23 Nov 2017
Cited by 3
Abstract
In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments [...] Read more.
In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
Development of a Shipboard Remote Control and Telemetry Experimental System for Large-Scale Model’s Motions and Loads Measurement in Realistic Sea Waves
Sensors 2017, 17(11), 2485; https://doi.org/10.3390/s17112485 - 29 Oct 2017
Cited by 2
Abstract
Wave-induced motion and load responses are important criteria for ship performance evaluation. Physical experiments have long been an indispensable tool in the predictions of ship’s navigation state, speed, motions, accelerations, sectional loads and wave impact pressure. Currently, majority of the experiments are conducted [...] Read more.
Wave-induced motion and load responses are important criteria for ship performance evaluation. Physical experiments have long been an indispensable tool in the predictions of ship’s navigation state, speed, motions, accelerations, sectional loads and wave impact pressure. Currently, majority of the experiments are conducted in laboratory tank environment, where the wave environments are different from the realistic sea waves. In this paper, a laboratory tank testing system for ship motions and loads measurement is reviewed and reported first. Then, a novel large-scale model measurement technique is developed based on the laboratory testing foundations to obtain accurate motion and load responses of ships in realistic sea conditions. For this purpose, a suite of advanced remote control and telemetry experimental system was developed in-house to allow for the implementation of large-scale model seakeeping measurement at sea. The experimental system includes a series of technique sensors, e.g., the Global Position System/Inertial Navigation System (GPS/INS) module, course top, optical fiber sensors, strain gauges, pressure sensors and accelerometers. The developed measurement system was tested by field experiments in coastal seas, which indicates that the proposed large-scale model testing scheme is capable and feasible. Meaningful data including ocean environment parameters, ship navigation state, motions and loads were obtained through the sea trial campaign. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle
A Search-and-Rescue Robot System for Remotely Sensing the Underground Coal Mine Environment
Sensors 2017, 17(10), 2426; https://doi.org/10.3390/s17102426 - 23 Oct 2017
Cited by 11
Abstract
This paper introduces a search-and-rescue robot system used for remote sensing of the underground coal mine environment, which is composed of an operating control unit and two mobile robots with explosion-proof and waterproof function. This robot system is designed to observe and collect [...] Read more.
This paper introduces a search-and-rescue robot system used for remote sensing of the underground coal mine environment, which is composed of an operating control unit and two mobile robots with explosion-proof and waterproof function. This robot system is designed to observe and collect information of the coal mine environment through remote control. Thus, this system can be regarded as a multifunction sensor, which realizes remote sensing. When the robot system detects danger, it will send out signals to warn rescuers to keep away. The robot consists of two gas sensors, two cameras, a two-way audio, a 1 km-long fiber-optic cable for communication and a mechanical explosion-proof manipulator. Especially, the manipulator is a novel explosion-proof manipulator for cleaning obstacles, which has 3-degree-of-freedom, but is driven by two motors. Furthermore, the two robots can communicate in series for 2 km with the operating control unit. The development of the robot system may provide a reference for developing future search-and-rescue systems. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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