scholarly journals Proximity Sensor for Thin Wire Recognition and Manipulation

Machines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 188
Author(s):  
Andrea Cirillo ◽  
Gianluca Laudante ◽  
Salvatore Pirozzi
Keyword(s):  
Tactile Sensor ◽  
Detection Algorithm ◽  
Accurate Estimation ◽  
Thin Wire ◽  
Shape Estimation ◽  
Software Applications ◽  
Touch Sensor ◽  
Grasping And Manipulation ◽  
Specific Object ◽  
Linear Object

In robotic grasping and manipulation, the knowledge of a precise object pose represents a key issue. The point acquires even more importance when the objects and, then, the grasping areas become smaller. This is the case of Deformable Linear Object manipulation application where the robot shall autonomously work with thin wires which pose and shape estimation could become difficult given the limited object size and possible occlusion conditions. In such applications, a vision-based system could not be enough to obtain accurate pose and shape estimation. In this work the authors propose a Time-of-Flight pre-touch sensor, integrated with a previously designed tactile sensor, for an accurate estimation of thin wire pose and shape. The paper presents the design and the characterization of the proposed sensor. Moreover, a specific object scanning and shape detection algorithm is presented. Experimental results support the proposed methodology, showing good performance. Hardware design and software applications are freely accessible to the reader.

scholarly journals Pothole Classification Model Using Edge Detection in Road Image

2020 ◽  
Vol 10 (19) ◽  
pp. 6662
Author(s):  
Ji-Won Baek ◽  
Kyungyong Chung
Keyword(s):  
Edge Detection ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Image Data ◽  
Structural Similarity ◽  
Detection Algorithm ◽  
Classification Model ◽  
Specific Object ◽  
Pixel Value ◽  
Distortion Rate

Since the image related to road damage includes objects such as potholes, cracks, shadows, and lanes, there is a problem that it is difficult to detect a specific object. In this paper, we propose a pothole classification model using edge detection in road image. The proposed method converts RGB (red green and blue) image data, including potholes and other objects, to gray-scale to reduce the amount of computation. It detects all objects except potholes using an object detection algorithm. The detected object is removed, and a pixel value of 255 is assigned to process it as a background. In addition, to extract the characteristics of a pothole, the contour of the pothole is extracted through edge detection. Finally, potholes are detected and classified based by the (you only look once) YOLO algorithm. The performance evaluation evaluates the distortion rate and restoration rate of the image, and the validity of the model and accuracy of the classification. The result of the evaluation shows that the mean square error (MSE) of the distortion rate and restoration rate of the proposed method has errors of 0.2–0.44. The peak signal to noise ratio (PSNR) is evaluated as 50 db or higher. The structural similarity index map (SSIM) is evaluated as 0.71–0.82. In addition, the result of the pothole classification shows that the area under curve (AUC) is evaluated as 0.9.

Force Characteristics for Fine Deformation of CMC Touch Sensor and Estimation of Force Variance Using Hybrid Tactile Sensor System

2012 ◽  
Vol 24 (3) ◽  
pp. 423-429
Author(s):  
Takuya Kawamura ◽  
◽  
Ko Nejigane ◽  
Kazuo Tani ◽  
Hironao Yamada
Keyword(s):  
Tactile Sensor ◽  
Force Sensor ◽  
Sensor System ◽  
Compression Force ◽  
Sensor Element ◽  
Silicon Rubber ◽  
Touch Sensor ◽  
Slight Movement ◽  
Force Characteristics

Having previously proposed a hybrid tactile sensor system consisting of a Carbon Micro-Coil (CMC) touch sensor and a force sensor, the authors have been developing a method of measuring deformation of micrometer order, force variance of 10 gram order, and compression force when an object touches a sensor element and moves slightly. In this paper, to measure the force variance for deformation of several micrometers using the CMC touch sensor, the force characteristics of the CMC touch sensor are investigated. The CMC sensor element is made of silicon rubber containing CMCs several micrometers in diameter. It is considered that the sensor element constitutes an LCR circuit, and the CMC touch sensor, deformed mechanically, produces signals due to the modification of the circuit. In the experiment detailed in this paper, to clarify the characteristics of the CMC sensor with respect to the parameters of force and deformation, the outputs of the CMC sensor and the force sensor for deformation in the range of 1 to 9 µm are sampled. As a result, it is found that the force characteristics of the CMC touch sensor are almost linear in terms of force variance within the range of 0 to 1 N, regardless of a compression force of less than 3 N. Finally, to evaluate the performance of the sensor system, force variance for a slight movement of an object touching the sensor element is estimated in an experiment.

Special Issue on Cybernetic City Transport Systems and Technologies

2010 ◽  
Vol 22 (6) ◽  
pp. 683-684
Author(s):  
Ljubo Vlacic ◽  
Toshio Fukuda ◽  
Yasuhisa Hasegawa ◽  
Michel Parent
Keyword(s):  
Building Blocks ◽  
Detection Algorithm ◽  
Operational Performance ◽  
Transport Systems ◽  
Shape Estimation ◽  
Sustainable Mobility ◽  
Dual Mode ◽  
Road Infrastructure ◽  
Traffic Lights ◽  
Road Testing

The publication of this issue was driven by the vision that, in the not too distant future, Cybernetic Transport Systems (CTS) will be seen on city roads and dedicated infrastructures. TheWorld Council for Sustainability has projected that CTS will be seen in cities in as early as 2030 (Mobility 2030: Meeting the Challenges to Sustainability; World Business Council for Sustainable Mobility, July 2004). CTS are based on fully automated driverless urban road vehicles (CyberCars). They can also be based on Dual-Mode Vehicles (DMV) - conventional vehicles with Advanced Driver Assistance Technology (ADAT) and capable of driverless driving, on request by a driver. ADAT covers electronic and software products that assist drivers in driving. DMV assumes that a driver is not in control of the vehicle at all times but is fully responsible for vehicle operation throughout. Both CyberCars and DMVs co-operate through vehicle-to-vehicle and vehicle-to-infrastructure communication links thus enabling cybernetic transport to achieve higher traffic flows and improve network efficiency. Main CTS building blocks are CyberCars and/or Dual Mode Vehicles, Road Infrastructure Elements and CTS Traffic Management & Control Centre. These four blocks are interconnected, integrated and made interoperable through Communication Architecture and Protocols, and Operational Safety & Reliability Certification Procedures. A variety of CTS concepts have been prototyped and evaluated within the scope of projects such as: (i) Toyota’s Intelligent Multimode Transportation System (http://www.expo2005.or.jp/en/technology/imts.html); (ii) the CyberCars (http://www.cybercars.org); CyberMove (http://www.cybermove.org); (iii) CityMobil (http://www.citymobil-project.eu/); (iv) Safespot (http://www.safespot-eu.org/); (v) CVIS (http://www.cvisproject.org); (vi) Group Rapid Transit (http://www.2getthere.eu/Group Transit). The figure above shows a CTS prototyped by the CyberCars-2 Project Consortium. An extensive infield, i.e., on-road testing of operational performance of co-operative cybernetic transport solutions was conducted at several road tracks, the last being held at La Rochelle, France, in September 2008. This issue addresses a broad spectrum of theoretical and implementational topics related to CTS development and deployment including: • Cooperative Cybernetic Transport System Architecture • Real-time Decision Making by driverless vehicles • On-road testing of operational performance of CTS • Road-Crossing Landmarks Detection algorithm • Landmark Shape Detection algorithm • Road Shape Estimation algorithm, and • Vehicle-to-road infrastructure (traffic lights) communication solutions. In addition, this issue presents papers that deal with ADAT and analyses: • Acceptability and Usability of a Parking Assistance System for Elderly Drivers • Relationships between Car Accidents and a Driver’s Physiology and Psychology • 2D Localization in Urban Environment, and • Sustainability and Reusability aspects of Common Robotic Technology components. We hope you enjoy the issue!

Remarks on the micro-earthquake detection problem: Refining the outcome using stochastic modeling

2020 ◽  
Author(s):  
Athanasios Lois ◽  
Fotis Kopsaftopoulos ◽  
Dimitrios Giannopoulos ◽  
Katerina Polychronopoulou ◽  
Nikos Martakis
Keyword(s):  
Seismic Noise ◽  
Computational Cost ◽  
Detection Algorithm ◽  
Body Waves ◽  
Autoregressive Models ◽  
Accurate Estimation ◽  
False Alarms ◽  
Small Magnitude ◽  
Ongoing Research ◽  
Wide Range

<p>Methodologies dealing with the detection of micro-earthquakes and the accurate estimation of body waves’ arrival time constitute, during the last decades, a topic of ongoing research. The extraction and efficient analysis of the useful information from the continuous recordings is of great importance, since it is a prerequisite for reliable interpretations.  Small magnitude seismic events, either naturally-occuring or induced, have been increasingly used in a wide range of industrial fields, with applications ranging from hydrocarbon and geothermal reservoir exploration, to passive seismic tomography surveys.</p><p>A great number of algorithms have been proposed and applied up to now for seismic event detection, exploiting specific properties of the seismic signals both in time and in frequency domain, with the energy-based detectors (STA/LTA) to be the most commonly used, due to their simplicity and the low computational cost they require. A significant obstacle emerging at seismological identification problems lies on the fact that such processes usually suffer from a number of false alarms, which is significantly increased in extremely noisy environments.</p><p>For that scope, we propose a “Decision-Making” mechanism, independent of the applied detection algorithm, which controls the results obtained during the detection process by minimizing false detections and providing the best possible outcome for further analysis. The specific scenario is based on the comparison among autoregressive models estimated on isolated seismic noise recordings, as well as on the detected intervals that resulted during the event identification procedure. A number of examples, associated with the implementation of the proposed scenario on real data, is presented with the scope of evaluating its performance. Several issues concerning the isolation of the seismic noise from the raw data, the estimation of the autoregressive models, the choice of the orders of the stochastic models etc., are discussed.</p>

Study of Pose Detection Algorithm for Specific Object Based on Monocular Vision

2014 ◽  
Vol 651-653 ◽  
pp. 517-523 ◽  
Author(s):  
Ling Yun Liu ◽  
Min Luo ◽  
Yue Min Wu
Keyword(s):  
Hausdorff Distance ◽  
Image Plane ◽  
Mathematic Model ◽  
Detection Algorithm ◽  
Monocular Vision ◽  
Threshold Method ◽  
Virtual Camera ◽  
Pose Detection ◽  
Specific Object ◽  
Vision Detection

This paper brings forward a monocular vision detection algorithm in allusion to the specific object’s pose based on Hausdorff Distance. At first, according to the mathematic model which has been established, the 2D template sequence is generated by projecting the specific object in different poses into the image plane of a virtual camera. Then, in order to predigest calculations and accelerate the matching speed during the image matching, the algorithm adopts the local-mean Hausdorff Distance as matching estimate and adopts the search strategy based on hiberarchy which reduces the searching rang by the threshold method before accurate match. In the end of this paper, the experiment that measures the poses of the clamp via the different clamp images respectively is given to testify the validity and speediness of this algorithm.

scholarly journals UAV low-altitude obstacle detection based on the fusion of LiDAR and camera

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Zhaowei Ma ◽  
Wenchen Yao ◽  
Yifeng Niu ◽  
Bosen Lin ◽  
Tianqing Liu
Keyword(s):  
Point Clouds ◽  
Detection Algorithm ◽  
Angle Measurement ◽  
Obstacle Detection ◽  
Accurate Estimation ◽  
Measurement Information ◽  
Depth Information ◽  
Performance Indexes ◽  
Low Altitude ◽  
Sensor Configuration

AbstractIn this paper, aiming at the flying scene of the small unmanned aerial vehicle (UAV) in the low-altitude suburban environment, we choose the sensor configuration scheme of LiDAR and visible light camera, and design the static and dynamic obstacle detection algorithms based on sensor fusion. For static obstacles such as power lines and buildings in the low-altitude environment, the way that image-assisted verification of point clouds is used to fuse the contour information of the images and the depth information of the point clouds to obtain the location and size of static obstacles. For unknown dynamic obstacles such as rotary-wing UAVs, the IMM-UKF algorithm is designed to fuse the distance measurement information of point clouds and the high precision angle measurement information of image to achieve accurate estimation of the location and velocity of the dynamic obstacles. We build an experimental platform to verify the effectiveness of the obstacle detection algorithm in actual scenes and evaluate the relevant performance indexes.

scholarly journals Tactile Sensor Data Interpretation for Estimation of Wire Features

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1458
Author(s):  
Andrea Cirillo ◽  
Gianluca Laudante ◽  
Salvatore Pirozzi
Keyword(s):  
Recognition Rate ◽  
Experimental Tests ◽  
Tactile Sensor ◽  
Data Interpretation ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Tactile Sensors ◽  
Straightforward Method ◽  
Place Task ◽  
Linear Object

At present, the tactile perception is essential for robotic applications when performing complex manipulation tasks, e.g., grasping objects of different shapes and sizes, distinguishing between different textures, and avoiding slips by grasping an object with a minimal force. Considering Deformable Linear Object manipulation applications, this paper presents an efficient and straightforward method to allow robots to autonomously work with thin objects, e.g., wires, and to recognize their features, i.e., diameter, by relying on tactile sensors developed by the authors. The method, based on machine learning algorithms, is described in-depth in the paper to make it easily reproducible by the readers. Experimental tests show the effectiveness of the approach that is able to properly recognize the considered object’s features with a recognition rate up to 99.9%. Moreover, a pick and place task, which uses the method to classify and organize a set of wires by diameter, is presented.

Mechatronics Design of Intelligent Robotic Gripper

2015 ◽  
Vol 649 ◽  
pp. 14-21 ◽  
Author(s):  
W.T. Asheber ◽  
Chyi Yeu Lin
Keyword(s):  
Tactile Sensor ◽  
Target Object ◽  
Robot Arm ◽  
Structural Elements ◽  
Direct Drive ◽  
System Complexity ◽  
Grasping And Manipulation ◽  
Grasping Force ◽  
Force Transmissibility ◽  
Crank Mechanism

This work presents multi-functional robot arm gripper design along with vision and tactile sensor for efficient grasping and manipulation tasks. The design emulates human’s hand fingers structure using linkages and direct drive through slider-crank mechanism transmission. The structural elements are optimized for a finest performance in motion and force transmissibility of the gripper fingers. The main future of this design is its reliability to grasp and manipulate unknown object while its system complexity is reduced. The gripper has a tool change fixture incorporated into its palm, which will reduce time wastage and do assembling in one go. The gripper is equipped with two cameras in its palm; subsequently it will efficiently seek the target object and perform its prehensile task with intelligently determined grasping force.

A New Highly Sensitive Dielectric Slip Detection Sensor for a Robotic Operation

2017 ◽  
Author(s):  
Sung Joon Kim ◽  
Ja Choon Koo
Keyword(s):  
Tactile Sensor ◽  
Relative Displacement ◽  
Large Area ◽  
Tactile Sensors ◽  
Post Process ◽  
Highly Sensitive ◽  
Grasping And Manipulation ◽  
Working Principle ◽  
Slip Detection

For dexterous grasping and manipulation, tactile sensors recognizing contact object are essential. Electronic skin (E-skin) with tactile sensors plays a role as both receiving information for grasping and protecting robot frame. This paper presents a polymer tactile sensor covering large area to fulfill role of E-skin. The sensor has a thin air gap between polymer layers and it is deformed reacting slip input. When slip is occurred, there is relative displacement between surrounding layer and it incurs change of electrode separation. NBR is used to sensor substrate because of its tough and flexible characteristic. Ultrathin aluminum tape is employed for electrodes. There is a changeability of size of the sensor because of its simple but effective working principle and structure. Slip detecting algorithm doesn’t have a post process such as FFT or DWT, so there isn’t delay for processing time. It realizes real-time slip detection reducing reaction time of robot hand.

2A2-F01 Manipulation of a Deformable Linear Object by an Unmanned Aerial Vehicle Based on Shape Estimation Using Catenary Curve

2015 ◽  
Vol 2015 (0) ◽  
pp. _2A2-F01_1-_2A2-F01_4
Author(s):  
Atsushi KUNO ◽  
Satoko ABIKO ◽  
Shota NARASAKI ◽  
Atsushi OOSEDO ◽  
Shohei KOKUBUN ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Shape Estimation ◽  
Aerial Vehicle ◽  
Catenary Curve ◽  
Linear Object
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