Sonar Sensors Research Articles

Robust and accurate monocular visual navigation combining IMU for a quadrotor

In this paper, we present a multi-sensor fusion based monocular visual navigation system for a quadrotor with limited payload, power and computational resources. Our system is equipped with an inertial measurement unit (IMU), a sonar and a monocular down-looking camera. It is able to work well in GPS-denied and markerless environments. Different from most of the keyframe-based visual navigation systems, our system uses the information from both keyframes and keypoints in each frame. The GPU-based speeded up robust feature (SURF) is employed for feature detection and feature matching. Based on the flight characteristics of quadrotor, we propose a refined preliminary motion estimation algorithm combining IMU data. A multi-level judgment rule is then presented which is beneficial to hovering conditions and reduces the error accumulation effectively. By using the sonar sensor, the metric scale estimation problem has been solved. We also present the novel IMU+3P (IMU with three point correspondences) algorithm for accurate pose estimation. This algorithm transforms the 6-DOF pose estimation problem into a 4-DOF problem and can obtain more accurate results with less computation time. We perform the experiments of monocular visual navigation system in real indoor and outdoor environments. The results demonstrate that the monocular visual navigation system performing in real-time has robust and accurate navigation results of the quadrotor.

Hybrid Motion Planning Method for Autonomous Robots Using Kinect Based Sensor Fusion and Virtual Plane Approach in Dynamic Environments

A new reactive motion planning method for an autonomous vehicle in dynamic environments is proposed. The new dynamic motion planning method combines a virtual plane based reactive motion planning technique with a sensor fusion based obstacle detection approach, which results in improving robustness and autonomy of vehicle navigation within unpredictable dynamic environments. The key feature of the new reactive motion planning method is based on a local observer in the virtual plane which allows the effective transformation of complex dynamic planning problems into simple stationary in the virtual plane. In addition, a sensor fusion based obstacle detection technique provides the pose estimation of moving obstacles by using a Kinect sensor and a sonar sensor, which helps to improve the accuracy and robustness of the reactive motion planning approach in uncertain dynamic environments. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles even in hostile environments where conventional method failed.

Sensor Technologies and Simultaneous Localization and Mapping (SLAM)

This paper presents a comprehensive review on sensor modalities currently in used for solving the Simultaneous Localization and Mapping (SLAM) problem. The review focuses on SLAM for mobile robots in a variety of environments. The strengths and weaknesses of acoustic modality sensors such as ultrasonic and sonar sensors, laser range finders, visual sensors such as stereo vision sensors, and RGB-D sensors like the Microsoft Kinect and the Asus Xtion Pro Live are compared based on current usage in published research papers. Based on this review, we propose that RGB-D sensors have unique advantages which make them particularly suitable for SLAM problems.

Cyber Aqua Culture Monitoring System UsingArdunio And Raspberry Pi

This paper aims at detecting the problems in aquaculture so that farmers can take preventive measures before things get out of control. It is designed to operate in ponds where aquatic animals are made to develop in their natural habitat. The device is provided with sensors namely Dissolved Oxygen sensor, PH sensor, Ultra Sonic Sensor, etc. which are connected to a base device called Arduino Board. The device uses the internet connectivity to regulate the works without manpower. In manmade ponds the Dissolved content of the oxygen, the PH level and the Water level varies with the density of the aquatic animals, so if the Dissolved oxygen content in the water decreases it will make the aquatic animals unable to survive in less oxygen atmosphere. The Dissolved oxygen sensor detects this and automatically switches on the aerators which then increase the content of oxygen. Similarly if the PH level of the water is below or above seven (7) the water becomes acidic or basic in nature which is not a good sign of natural habitat for animals. The PH level sensor detects this and we can take counter measures to make the PH again to 7. We can also regulate the temperature of the water using temperature sensor.

English

English

Evidence Supporting Measure of Similarity for Reducing the Complexity in Information Fusion

This paper presents a new method for reducing the number of sources of evidence to combine in order to reduce the complexity of the fusion processing. Such a complexity reduction is often required in many applications where the real-time constraint and limited computing resources are of prime importance. The basic idea consists in selecting, among all sources available, only a subset of sources of evidence to combine. The selection is based on an evidence supporting measure of similarity (ESMS) criterion which is an efficient generic tool for outlier sources identification and rejection. The ESMS between two sources of evidence can be defined using several measures of distance following different lattice structures. In this paper, we propose such four measures of distance for ESMS and we present in details the principle of Generalized Fusion Machine (GFM). Then we apply it experimentally to the real-time perception of the environment with a mobile robot using sonar sensors. A comparative analysis of results is done and presented in the last part of this paper.

MSRDS 플랫폼에서 로봇 센서들의 성능 비교분석

MSRDS(Microsoft Robotics Developer Studio), the robot simulation platform provides the simulation robots and environments enabling to the basic robot programming without hardware robots. In this paper, we carry the maze escaping problems to compare and analyze the performance of LRF, bumper, IR, and sonar sensor with the same condition on MSRDS(Microsoft Robotics Developer Studio) environment. To evaluate the performance of sensors, we program the simulation environments with same conditions for all sensors. We could find that the LRF sensor had the highest performance and the bumper sensor has the lowest performance on the travel time, the number of turning, and the number of collisions. It was also confirmed that IR sensor and sonar sensor had lower performance than LRF sensor on the number of turning.

Impedance control of a small treadmill with sonar sensors for automatic speed adaptation

Automatic speed adaptation in treadmill training plays an important role in gait rehabilitation and virtual reality (VR) environments, where the user can adjust his/her speed for improved motivation and an enhanced sense of reality during walking interactions. To implement automatic speed adaptation of a treadmill belt, we have developed a novel impedance control scheme that accommodates natural movements without mechanical attachments to the user, and can estimate user-treadmill interactive forces to directly detect user intention, while simultaneously maintaining the user’s position on the treadmill platform. The proposed impedance control is realized via user interaction with a fixed virtual spring-damper component, allowing direct acceleration control of the treadmill belt in proportion to user displacement. The technique was applied to a small commercial treadmill (with a belt length of 1.2 m and a width of 0.5 m), which is easily installed and economical to operate, and is widely used in homes and health centers. Inexpensive sonar sensors with a Kalman filter algorithm were employed to measure user motions. To identify the characteristics of the proposed control scheme, a set of experiments was conducted and preliminary user studies with VR interactions were performed. The results of these experiments indicate that our impedance control scheme can provide a non-intrusive, intuitive method for implementing user-selected speed on a small treadmill. The proposed technique is cost-effective, and could potentially be applied to any type of locomotion interface or gait rehabilitation system, without the use of expensive, sophisticated sensors or special treadmills.

Intelligent Indoor Mobile Robot Navigation Using Stereo Vision

Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a map of the corresponding environment. Stereo vision, while still being a rapidly developing technique in the field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This paper aims at describing an experimental approach for the building of a stereo vision system that helps the robots to avoid obstacles and navigate through indoor environments and at the same time remaining very much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors which helps in the successful navigation through different types of complex environments. The data from the sensor enables the robot to create the two dimensional topological map of unknown environments and stereo vision systems models the three dimension model of the same environment.

Calibration of a spinner anemometer for yaw misalignment measurements

AbstractThe spinner anemometer is an instrument for yaw misalignment measurements without the drawbacks of instruments mounted on the nacelle top. The spinner anemometer uses a non‐linear conversion algorithm that converts the measured wind speeds by three sonic sensors on the spinner to horizontal wind speed, yaw misalignment and flow inclination angle. The conversion algorithm utilizes two constants that are specific to the spinner and blade root design and to the mounting positions of the sonic sensors on the spinner. One constant, k2, mainly affects the measurement of flow angles, while the other constant, k1, mainly affects the measurement of wind speed. The ratio between the two constants, kα=k2/k1, however, only affects the measurement of flow angles. The calibration of kα is thus a basic calibration of the spinner anemometer.Theoretical background for the non‐linear calibration is derived from the generic spinner anemometer conversion algorithm. Five different methods were evaluated for calibration of a spinner anemometer on a 500 kW wind turbine. The first three methods used rotor yaw direction as reference angular, while the wind turbine, was yawed in and out of the wind. The fourth method used a hub height met‐mast wind vane as reference. The fifth method used computational fluid dynamics simulations. Method 1 utilizing yawing of the wind turbine in and out of the wind in stopped condition was the preferred method for calibration of kα. The uncertainty of the yaw misalignment calibration was found to be 10%, giving an uncertainty of 1° at a yaw misalignment of 10°. © 2014 The Authors. Wind Energy published by John Wiley & Sons, Ltd.

Bayesian multiple target tracking, 2nd edition [Book review

Any book with the word in the title is worth a look. In this case, we are rewarded by a carefully crafted volume that explains a plethora of useful algorithms for multiple target tracking. The second edition has gained two authors and lost one. The first edition (1999) did not mention particle filters, but the new edition includes good references and discussions of this important new technology. The text is very clear, accessible, and well organized, reflecting the education of the authors (50% with doctorates in math and 50% in mathematical statistics). The book includes many practical examples from sonar, radar, and other sensors. Approximately 75% of the authors have been experts at real-world sonar tracking for many decades. The authors carefully and politely explain why they use Bayesian methods rather than fuzzy logic, Dempster-Shafer theory, or imprecise probability, but this explanation is perhaps too polite for my taste. It is refreshing to read a book that does not erroneously assert that Dempster-Shafer theory or fuzzy logic is more robust and more general than Bayesian methods. The table on page 157 nicely summarizes the methods, outputs, and assumptions of the tracking methods considered (e.g., multiple hypothesis tracking [MHT], joint probabilistic data association [JPDA], and probabilistic MHT), but in the eagerly awaited third edition, one would like to see other methods included, such as the boring old nearest-neighbor data association, nearest-neighbor JPDA, single-scan assignment, multiscan assignment, the Hough transform, and various favors of retrodiction.

Embedded System Application for Blind People Navigation Tool

The stick for blindman navigational aid can only provide information about the presence of objects that being touched. This navigational aid stick can not provide more information such as object distance and the name of the place. To overcome this problem, we realized a navigational tool that can provide information about the distance of objects around the user and the name of the places where being passed. The existing objects are detected using three sets of ultra sonic sensors. These sensors emit ultrasonic signals, when the signal collide the obstacle, then will be reflected back and being received by these sensors too. The time lag between the transmitting and receiving signals then will be converted into the distance. RFID reader is used to read the presence or absence of tags around the RFID reader. Identity tag emits a signal that will be used to mark the place name. The results of measuring distance and sequence voice database recorder gives a good yield. Voice database recorder circuit works as well as the detection of RFID tags.

Real-Time 3D Simulation for the Trawl Fishing Gear Based on Parallel Processing of Sonar Sensor Data

A huge and a complex internal computation is required to visualize the underwater geometry of a fishing gear, because each particle of the gear should be calculated with consideration of several force vectors, such as the movements of the fishing vessel, the buoyancy of the gear, and the tension of pulling or pursing acting on the net panels. The internal computation is the main drawback for providing a real-time visualization that takes into account the force vectors and the changes of underwater environments which can be obtained from the multiple sonar sensors. This paper presents a three-dimensional (3D) visualization tool that offers real-time simulations of the trawl fishing gear using parallel processing for the particles applying the force vectors. This tool also offers different underwater geometries for each fishing gear through a multiview display. The tool employs OpenMP APIs and OpenGL libraries to calculate in parallel the particles and to draw the underwater shapes of fishing gears, respectively. This work can be applied to other simulation systems for analyzing the precise model of graphical geometries as well as modeling the underwater shapes of fishing gears.

시간지연 제어기를 이용한 쿼드로터 시스템의 고도제어에 대한 연구

This paper presents the altitude control of a quadrotor system under the disturbance. The altitude is measured by an ultra sonic sensor attached at the bottom of the quadrotor system and the measured altitude data are used in the time-delayed controller. To test the robustness of the controller, a weight attached to the center of the system is dropped intentionally several times to cause disturbances to the system. Performances of the altitude control by the PID control and time-delayed control method are compared experimentally. Experimental studies are conducted to verify the outperformance of the time-delayed controller for controlling the altitude of the quadrotor system under disturbances.

VISTA: achieving cumulative VIsion through energy efficient Silhouette recognition of mobile Targets through collAboration of visual sensor nodes

Visual sensor networks (VSNs) are innovative networks founded on a broad range of areas such as networking, imaging, and database systems. These networks demand well-defined architectures in terms of sensor nodes and camera deployment, image capturing and processing, and well-organized distributed systems. This makes existing VSN architectures deficient because these are limited in approach and in design. In this paper, we propose VISTA, a distributed vision multi-layer architecture aimed at constructing the cumulative vision of mobile objects (MOs). VISTA realizes silhouette recognition of mobile targets through (a) pre-meditated deployment of sensor nodes (SNs) that are equipped with sonar sensors and fixed view (FV) on-board cameras present at the periphery of region of interest (RoI) and SNs with only on-board cameras within RoI, (b) pre-distribution of silhouettes of known objects across SNs, (c) sonar-based presence detection of MO at the outskirts of RoI, (d) MO silhouette capturing and matching at interior node to determine the % age match, (e) subsequent activation of next interior cameras in order to improve % age match, and (f) terminating further activation upon threshold recognition of MO. Experimental evaluation of our image processing algorithms against baseline algorithms with respect to execution time and memory shows significant reduction in image data and memory occupancy. Also, experiments show that true match is achieved fully under broad daylight conditions and large backgrounds when our proposed background subtraction and pixel reduction techniques are used. The mobility-driven behavior of associated network layer algorithms of VISTA is simulated in a network simulator (NS2) by representing the surety of MO identification as a function of number of cameras, database size and distribution, MO’s trajectory, stored perspectives, and network depth. The simulation results show that doubling and, in some situations, manifold increase is observed in the surety of the target with an increase in the number of silhouettes deployed against the baselined database size and mobility model. The results substantiate that VISTA is a suitable architecture for low-cost, autonomous and efficient human and asset monitoring surveillance, friend-or-foe (FoF) identification, and target tracking systems.

Estimating Object Location using Particle Clustering on Rotating Sonar Detection

Particle filter been used for localization and position estimation with various applications. Several method applied in order to reduce the complexity of particle information to lower processing resource requirement while providing a precise map. Sonar sensor provide a range precision with poor bearing. Partial observation applied to gain estimation of object location using several measurement from multiple vantage point. This paper propose grouping of detection particle from sonar sensor using clustering method in order to provide estimated object position from a single vantage point. The approach estimate objects using euclidean distance treshold to separate one object detections from the other and group all the detection particle into cluster containing a set of number. As a result of particle clustering, object location can be estimated with their respective weight of certainty as an attribution for further decision making.

Avoiding Obstacle Control of Mobile Robot Based on Artificial Potential Field Method

Avoiding obstacle control strategy of Mobile robot based on Artificial Potential Field is addressed in this paper, detecting ambient by use of sonar sensor .Setting target point and the moving speed arbitrarily in mobile simulation environment, these avoid obstacle moment are conducted successfully.

Implementing Autonomous Navigation Robot for building 2D Map of Indoor Environment

ABSTRACT This paper solves the problems of Simultaneous localization and mapping (SLAM) that deals with local path planning of an autonomous mobile robot in indoor environment, by using sonar sensors for object detection and range information, and also uses wheel encoders for tracking robot position and orientation based on dead-reckoning process. In this work, mobile robot uses wall-follower technique for an autonomous navigation in unknown indoor environment. This is based on the behavior of the mobile robot developed for fully automatic navigating beside the wall without shocking it and also avoids hitting any obstacles during navigation near the wall. This work involves the construction of control algorithm, which has four functions: follow the wall, obstacles avoidance, determine the location of mobile robot simultaneously with building 2D map within an unknown environment. Two cases were described in this project, the result of first case showed how mobile robot can navigated successfully without supervisor in two mini room and corridors and showed how the robot with sonar can drew this area during navigation, the result of second case showed how mobile robot could navigate successfully without supervisor in room with three obstacles and showed how mobile robot with sonars could drew these obstacles with walls of plan during navigation. Both cases used wall following techniques for navigation to follow the walls and avoided all obstacles that are located on its way.

Quality assurance of diaphragm walls by sonar measurements – model study

Diaphragm walls are used to provide a stable and water-tight confinement for the construction of tunnels, underground railway stations, deep basements and other structures requiring deep excavations. These walls consist of individual panels, cast piece-wise in the ground, separated by water-tight joints. There are several methods to improve the water tightness of these joints, including rubber bands, metal sheets or precast concrete elements. In most cases, diaphragm walls perform very well. Quality problems, which occur in a few occasions, may be due to uncontrolled concrete flow between the joints, unexpected geological conditions or poor workmanship. Different methods of quality assurance are applied on construction sites. Sonar instruments can be used in a bentonite-filled trench to evaluate the shape of the excavation. An improved prototype instrument has been developed, including digital data-processing features, which allow the detection of even small anomalies at the stop-end surface before concreting the adjacent panel. The sonar sensor can be used in depths up to 200 m. Model experiments show that a centimetre resolution can be achieved. Set-up, model experiments and their results are shown. The prototype might be the basis of an easy-to-use commercial device.

Two-Dimensional Sensor System for Automotive Crash Prediction

This paper focuses on the use of magnetoresistive and sonar sensors for imminent collision detection in cars. The magnetoresistive sensors are used to measure the magnetic field from another vehicle in close proximity, to estimate relative position, velocity, and orientation of the vehicle from the measurements. First, an analytical formulation is developed for the planar variation of the magnetic field from a car as a function of 2-D position and orientation. While this relationship can be used to estimate position and orientation, a challenge is posed by the fact that the parameters in the analytical function vary with the type and model of the encountered car. Since the type of vehicle encountered is not known a priori, the parameters in the magnetic field function are unknown. The use of both sonar and magnetoresistive sensors and an adaptive estimator is shown to address this problem. While the sonar sensors do not work at very small intervehicle distance and have low refresh rates, their use during a short initial time duration leads to a reliable estimator. Experimental results are presented for both a laboratory wheeled car door and for a full-scale passenger sedan. The results show that planar position and orientation can be accurately estimated for a range of relative motions at different oblique angles.