Relative Position Measurements Research Articles

Improved Accuracy of Projected Marker Measurement in Relative Position and Posture Measurement for UAV

Improved Accuracy of Projected Marker Measurement in Relative Position and Posture Measurement for UAV

Localization and Tracking Control of Autonomous Vehicles in Time-Varying Bearing Formation

This letter proposes an observer-based formation tracking control approach for multi-agent velocity-controlled vehicles under the assumption that either relative or global position measurements are unavailable for all the vehicles. It is assumed that only some vehicles (at least one) have access to their own global position, and all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles. Each vehicle estimates its global position using relative bearing measurements and estimates of neighboring vehicles received over a communications network. Then, a distributed output-feedback observer-based controller is designed relying on bearing measurements and the estimated global positions. In contrast with the literature on bearing-based localization and control, we relax the common assumption of so-called bearing rigidity, and, in addition, we do not assume that the interconnections are constant. To the best of our knowledge, the bearing-based localization-and-tracking control problem under such assumptions remains open. In support of our theoretical findings, some simulation results are presented to illustrate the performance of the proposed observer-based tracking controllers.

Application and Assessment of Cooperative Localization in Three-Dimensional Vehicle Networks

The trajectory planning and control of multi-agent systems requires accurate localization, which may not be possible when GPS signals and fixed features required for SLAM are not available. Cooperative Localization (CL) in multi-agent systems offers a short-term solution that may significantly improve vehicle pose estimation. CL algorithms have been mainly developed and assessed for planar mobile robot networks due to complexities and singularities in three-dimensional (3D) motion. In this paper, we develop the required singularity-free equations and apply and assess an EKF-based CL for 3D vehicle networks. We assess the performance of CL with respect to the number of simultaneous and redundant measurements. We further assess CL performance with only relative position measurements available. Finally, experiments are performed to validate the proposed algorithms. We further investigate the effect of absolute position measurements in CL. Conclusions: Cooperative localization is an effective method when applied to 3D vehicle networks. However, CL does not improve localization with only relative position measurements, and thus previously reported results for 2D vehicle models were only effective due to relative orientation measurements. Absolute measurement reduces the overall localization errors much more significantly when there has been CL with prior relative position measurements.

Stabilizing Angle Rigid Formations With Prescribed Orientation and Scale

Angle rigid formations have the advantage of requiring only local bearing/direction measurements in their implementation. However, the capability of controlling the orientation and scale of these formations has not been explored. This undetermined orientation and scale can degrade the robustness of the formation against measurement noise. To maintain both advantages of requiring less sensor measurements and sustaining robustness against measurement noise, this article aims to achieve a desired angle rigid formation while simultaneously controlling its orientation and scale. In this article, we first design a formation algorithm for the first three agents to achieve a desired triangular formation with prescribed orientation and scale. Using the control gain design technique, we then design formation control algorithms for the remaining agents such that the overall desired formation can be achieved under a vertex addition operation. We present the role of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">generic</i> property from angle rigidity for the formation’s stability analysis. We also highlight that with one additional relative position measurement or two additional communication channels, the local convergence to the corresponding desired formation can be improved to a global convergence. Experiments are conducted to validate the theoretical results and the advantages are highlighted in comparison with other two formation control laws.

Distributed Path Tracking for Autonomous Underwater Vehicles Based on Pseudo Position Feedback

In this paper, we consider the distributed polynomial path tracking problem for a swarm of autonomous underwater vehicles (AUVs) modeled by second-order uncertain multi-agent systems. The application scenario of this paper has three distinguished characteristics. First, the communication network for the multi-agent system is unreliable and switching. Under the jointly connected condition, the communication network can be disconnected the entire time. Second, it is supposed that only the relative position between AUVs can be obtained for trajectory tracking control. Third, the AUV dynamics are subject to uncertain system parameters. By applying the cooperative output regulation control framework, a novel distributed robust control scheme is proposed to solve the distributed path tracking problem, which consists of three parts. First, to cope with communication network uncertainty, the distributed observer was invoked to recover the polynomial path for each AUV. Second, based on the relative position measurement between AUVs, a pseudo position estimator was adopted to generate the pseudo position for each AUV. Finally, based on the estimated polynomial path and the pseudo position, a certainty equivalent robust internal model control law was synthesized to achieve asymptotic reference trajectory tracking, where the internal model compensator aims to tackle uncertain system parameters. Numerical simulations are provided to validate the effectiveness of the proposed control scheme.

Model-Based Cooperative Navigation for a Group of Flying Robots

In this article, a model-based cooperative navigation system for a group of quadrotors, while no absolute position data is accessible, is proposed. The growth of position errors in a GNSS-denied condition is such that the navigation methods are not reliable. In the proposed method, instead of the conventional inertial navigation equations, a different dynamic equation based on drag forces is used. Together with the relative position measurements between agents, the acceleration measurements on the plane of the rotors of at least one of the agents are also used in the observation process. For evaluation of the proposed method, an algorithm-in-loop 6DOF simulation environment is developed. The results illustrate that the growth rate of navigation errors is significantly reduced; 97% in the horizontal plane and 40% in the vertical one. In short, integrating the proposed model-based and cooperative navigation methods is more effective than using each of them separately.

Clustering of distance sensors to transfer training data for relative position and orientation measurement devices

Car-sharing services have recently attracted considerable attention. We proposed a platooning system to reduce the number of vehicle distributors. The platooning system uses a measurement device embedded with low-cost infrared distance sensors to measure the relative position and orientation of vehicles. The relative positions and orientations are obtained from the training data. However, preparing training data is time consuming. In this study, a sensor clustering method that selects sensors with similar output characteristics is proposed. Consequently, a set of training data are used repetitively for all relative positions and orientation measurement devices embedded with sensors with similar output characteristics. The verification experiment of the sensor clustering revealed that the calculation range restriction is the key technique. Platooning has been successful in various courses by using sensors with similar output characteristics. Based on the results, the proposed clustering method can effectively collect sensors with similar output characteristics and it realizes the training data transfer to the newly manufactured devices. In addition, it has the potential to improve production efficiency for the mass production of relative position and orientation measurement devices.

Monocular-Based Pose Estimation Based on Fiducial Markers for Space Robotic Capture Operations in GEO

This paper tackles the problem of spacecraft relative navigation to support the reach and capture of a passively cooperative space target using a chaser platform equipped with a robotic arm in the frame of future operations such as On Orbit Servicing and Active Debris Removal. Specifically, it presents a pose determination architecture based on monocular cameras to deal with a space target in GEO equipped with retro-reflective and black-and-white fiducial markers. The proposed architecture covers the entire processing pipeline, i.e., starting from markers’ detection and identification up to pose estimation by solving the Perspective-n-Points problem with a customized implementation of the Levenberg–Marquardt algorithm. It is designed to obtain relative position and attitude measurements of the target’s main body with respect to the chaser, as well as of the robotic arm’s end effector with respect to the selected grasping point. The design of the configuration of fiducial markers to be installed on the target’s approach face to support the pose determination task is also described. A performance assessment is carried out by means of numerical simulations using the Planet and Asteroid Natural Scene Generation Utility tool to produce realistic synthetic images of the target. The proposed approach robustness is evaluated against variable illumination scenarios and considering different uncertainty levels in the knowledge of initial conditions and camera intrinsic parameters.

Cooperative Localization Using the 3D Euler–Lagrange Vehicle Model

Kalman filter-based cooperative localization (CL) algorithms have been shown to significantly improve pose estimations within networks of vehicles but have relied predominantly on two-dimensional kinematic models of the member agents. An inherent deficiency of the commonly employed kinematic vehicle model is the ineffectiveness of CL with only relative position measurements. In this work, we present a singularity-free CL using the full three-dimensional (3D) nonlinear dynamic vehicle model suitable for decentralized control and navigation of heterogeneous networks. We develop the algorithm, present Monte Carlo simulation results with relative pose measurements, and assess the algorithm performance as the number of measurements increases. We further demonstrate that CL with only relative position measurements is effective when using the dynamic model and benefits from increasing number of measurements. We also evaluate the performance of CL with respect to measurement task distribution, which is important in cooperative control of autonomous vehicles.

Maneuvering Angle Rigid Formations With Global Convergence Guarantees

Angle rigid multi-agent formations can simultaneously undergo translational, rotational, and scaling maneuvering, therefore combining the maneuvering capabilities of both distance and bearing rigid formations. However, maneuvering angle rigid formations in 2D or 3D with global convergence guarantees is shown to be a challenging problem in the existing literature even when relative position measurements are available. Motivated by angle-induced linear equations in 2D triangles and 3D tetrahedra, this paper aims to solve this challenging problem in both 2D and 3D under a leader-follower framework. For the 2D case where the leaders have constant velocities, by using local relative position and velocity measurements, a formation maneuvering law is designed for the followers governed by double-integrator dynamics. When the leaders have time-varying velocities, a sliding mode formation maneuvering law is proposed by using the same measurements. For the 3D case, to establish an angle-induced linear equation for each tetrahedron, we assume that all the followers' coordinate frames share a common <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Z$</tex> direction. Then, a formation maneuvering law is proposed for the followers to globally maneuver <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Z$</tex> -weakly angle rigid formations in 3D. The extension to Lagrangian agent dynamics and the construction of the desired rigid formations by using the minimum number of angle constraints are also discussed. Simulation examples are provided to validate the effectiveness of the proposed algorithms.

Bearing-based formation tracking control of AUVs with optimal gains tuning

This paper investigates the bearing-based formation tracking control problem of multiple autonomous underwater vehicles (AUVs), where the linear velocity and actuator constraints are considered. Different from the existing control methods for AUVs, position or relative position measurements are not required in our work. A leader-follower structure is adopted, where the leaders move with a time-varying and unknown linear velocity in the earth-fixed frame. We propose a consensus-based orientation estimator and an adaptation law for estimating the leaders’ linear velocity in the leaders’ common body-fixed frame, respectively. Then, a bearing-based formation tracking controller is designed for the followers to track the leaders and achieve the desired formation shape. Using cascade system theories, the global asymptotic stability of the overall system is rigorously analyzed. Furthermore, the estimator gains and controller gains are determined by the proposed optimal gains tuning method such that the prescribed performance criteria are optimized while satisfying the linear velocity and actuator constraints. Hence, stability, optimality, and feasibility are all achieved. Some simulation results are also given to demonstrate the effectiveness of our method.

Methods of mutual high-precision navigation based the use of relative modes of anglemeasuring receivers of global navigation satellite systems signals

The article presents the results of experimental studies of mutual high-precision navigation methods for unmanned and specialized transport systems. The proposed methods are based on the application of the relative operating modes of two or more angle-measuring receivers of global navigation satellite systems signals. To conduct research, a software and hardware complex has been developed, consisting of two angle-measuring receivers of global navigation satellite systems signals, a turntable and a computer model of the navigation system of unmanned and specialized transport systems. It provides the positioning error of the antenna system in angular coordinates less than 1 arc minute, which allows it to be used as a reference when measuring the angular displacements of the receiver of global navigation satellite systems signals antenna system. The results of measurements of planar and angular coordinates both in autonomous and relative phase modes of operation of goniometric receivers global navigation satellite systems signals are presented and analyzed. It has been established that the root-mean-square error of measuring relative coordinates was 0,019 meter. A further increase in the relative position measurement accuracy is possible by taking measures to reduce the multipath reception error, which is the most significant uncorrelated position measurement error by two sets of receivers of global navigation satellite systems signals. Thus, the methods of mutual high-precision navigation using angle-measuring receivers of global navigation satellite systems signals have high accuracy without the use of external information about differential corrections. This will allow the operation of unmanned or special transport systems in hard-toreach and northern regions, in conditions of lack of communication and other adverse factors.

Autonomous hanging tether management and experimentation for an unmanned air‐surface vehicle team

AbstractThe mission of an unmanned air vehicle (UAV) tethered to a small unmanned surface vehicle (USV) is considered. As opposed to the majority of existing tethered UAV work, which assumes a taut tether, this paper addresses the challenge of tether management for a slack, hanging tether in a dynamic ocean environment up to sea state 4 on the Douglas scale. A prototype smart reel system for a UAV–USV team was designed and experimentally validated in controlled and uncontrolled dynamic environments. A reference model for tether control based on static catenary cable theory was extended and shown to be valid through the entire operational envelop. A Kalman filter was developed to fuse slow (4 Hz) differential GPS (dGPS) relative position measurements with fast (100 Hz) inertial measurements, to output a 100 Hz estimate of relative position, relative velocity, and inertial sensor bias. A relative velocity‐based gain‐scheduled proportional‐derivative (PD) controller was developed, and demonstrated robustness to heave, pitch, and roll motion of the USV. Experimental testing with a UAV surrogate showed successful decoupling of heave motion from the UAV altitude in a controlled indoor environment. Taut tether control, in contrast, exhibited 12 times more tether tension at the UAV compared to the controller proposed here. The performance of the tuned controller with feedback from the Kalman filter exhibited minimal deviation from static catenary cable theory during the dynamic experiments. Indoor flight testing showed the developed reference model and controller essentially decoupled the dynamic motion of the USV from that of the UAV; the measured deflections of the UAV altitude and position essentially matched that of untethered flight. Outdoor flights validated the effectiveness of the controller in an unknown dynamic environment, for a larger relative position between the UAV and USV, using the dGPS Kalman filter solution to measure relative position. Initial experimental results look promising for continued on‐water testing of hanging‐tether UAV/USV teams.

A New Fiber Detection Method for LAMOST Based on the Front-illuminated Method

The double revolving fiber positioning technology is one of the key technologies for the success of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). The accuracy of fiber positioning will directly affect the observation efficiency of LAMOST. To achieve higher fiber positioning accuracy, the original open-loop controlled fiber positioning system urgently needs to be upgraded into a closed-loop control system. The fiber detection is the most important part of the closed-loop controlled fiber positioning system. The back-illuminated detection method is usually used to detect the fiber position by directly detecting the light spot generated at the fiber end in the multi-fiber spectral surveys. In this paper, we introduce a new method to measure the fiber position based on the image of the front-illuminated LAMOST focal plane. The front-illuminated image does not require lighting devices inside the spectrograph, and it could reduce the instability and light pollution in the spectrograph end. Our method measures the fiber position by fitting the profile of the fiber pinhole with a 2D Gaussian function. A series of tests show that the relative position measurement precision of the front-illuminated method is about 0.″12, and the method could have the same accuracy as the back-illuminated method once the system bias is calibrated by a simple radial correction function. The required fiber positioning accuracy of LAMOST is 0.″4, and the new method satisfies the requirement of LAMOST fiber detection accuracy and could be used in the closed-loop fiber control system.

An Off-Board Vision System for Relative Attitude Measurement of Aircraft

Aircraft attitude has always been an important technical parameter during flights, especially for stages such as aircraft take-off and landing. This article presents a monocular off-board vision system for relative attitude measurement of fixed-wing aircraft. In this system, a zoom imaging subsystem is set up to track and shoot the aircraft over a large distance range. Image sequences and corresponding servo data are transmitted to the processing computer for vision algorithms. A model-based attitude tracking algorithm, which requires the computer-aided design model of the aircraft, is performed to measure the relative attitude of the aircraft with respect to the reference platform. A 2-D visual tracking algorithm and a target detection algorithm are also employed to control the vision system. The proposed attitude tracking algorithm achieves competitive results on a publicly available dataset. The full system is validated in a real-flight experiment. The results revealed that the proposed system can run in real time on 1920×1080@40 Hz videos with an accuracy better than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> .

Graph-based observability analysis for mutual localization in multi-robot systems

In this paper, we investigate the observability properties of a type of nonlinear system, which often arises from multi-robot mutual localization problems. An extended relative position measurement graph (ERPMG) is constructed to integrate all influencing factors of observability, including the motion inputs and relative position measurements of robots. We analyze the observability of such systems by bridging the connection between the nonlinear observability matrix and the spectral matrix of the ERPMG. A necessary and sufficient observability condition for MRS represented by spectral graph properties of the ERPMG is derived for the first time. We then develop an algorithm to efficiently check the observability and further validate the proposed theoretical results by simulation experiments.

Robust Adaptive Consensus of Decentralized Large-Scale Bi-Directional Vehicular Platoons With Only Relative Position Measurement

This paper presents a new approach to solve the problem of internal and string stability of decentralized large-scale bi-directional vehicular platoons (DLBVPs) under uncertain dynamics with constant spacing strategy. It is assumed that each following vehicle can only measure the relative position with respect to its predecessor and subsequent vehicles. To estimate the uncertain dynamics of each following vehicle and unknown leader acceleration, a new decentralized robust adaptive consensus protocol is introduced which by using only relative position measurement, guarantees internal and string stability. It will be shown that the control gains are tuned without requiring any knowledge about the platoon size (number of following vehicles) and consequently, the controller is robust against size changing due to common maneuvers. By using Lyapunov theorem, we will prove that under this approach, the position and velocity tracking errors of each vehicle converge to zero asymptotically. Furthermore, it is shown that the adaptation laws have the main role in assuring string stability of DLBVPs with constant spacing strategy. Several simulation and practical results will depict the merits of this algorithm.

Relative Position and Posture Measurement Using Projected Markers

In recent years, demand for UAVs has been increasing in various situations such as aerial photography, infrastructure inspections of bridges, and logistics. In this study, we focus on bridge inspections in non-GPS environments and propose a measurement method using a projected marker and camera that enables self-position estimation. This measurement method aims to solve the problem of the large measurement error of position and posture as the shooting distance increases by using "laser parallelism correction". Experiments were conducted using a measurement unit consisting of a laser pointer, a camera, and a projection plane, and image processing software was used to analyze the captured images. The experiment was conducted by measuring the position of the projection plane at several shooting distances and changing the posture of the projection plane at each shooting distance to measure the posture. As a result, we succeeded in reducing the measurement error, which had been a problem in previous studies, by using laser parallelism correction, and confirmed the effectiveness of this method.

GEZGİN ROBOTLARIN İÇ ORTAMDA SEYRÜSEFERİ İÇİN SIKI BAĞLI BİR BAŞ AÇISI VE KONUMLANDIRMA SİSTEMİ

This study shows the effectiveness of data fusion techniques to achieve robust heading and position information in localization systems. The proposed system that has tightly coupled structure calculates heading and position of the mobile robot using the absolute and relative positioning subsystems. The relative positioning subsystem obtains heading and position information by using the odometry information and kinematic model of the robot. Absolute positioning subsystem, calculates position and rough heading information using ultrasonic signals. In this study, firstly the robust heading information is calculated by combining absolute and relative heading with conventional Kalman Filter. And then the correction on the relative position measurement has been made by using this robust heading information. Finally, in order to better positional information, an adaptive Kalman filter is applied for fusing the the absolute position and the corrected relative position. In the experimental study, the positional accuracy and precision of the system is obtained as 63 mm and 86% (for positional error

Robust noncooperative attitude tracking control for rigid bodies on rotation matrices subject to input saturation constraint

AbstractThis paper addresses the noncooperative attitude tracking control problem for rigid bodies whose dynamics evolves on the rotation matrix . First, based on the relative attitude measurement, a saturated angular velocity input is designed by a proposed saturated nonlinear function. Thereafter, the attitude tracking control torque for rigid body's dynamics with input saturation constraint and active disturbance rejection is developed by a modified dynamic surface control approach which can avoid large torque in practice. Furthermore, by using only relative attitude measurements, two types of velocity‐free attitude control laws are considered, respectively. In contrast to those control schemes that require that the desired angular velocity is available to the rigid body, the proposed scheme is able to solve the attitude control in noncooperative scenarios, where the desired angular velocity and acceleration are not accessible. Since the attitude described by rotation matrix enables the controller to use local measurements in the body‐fixed frame rather than global measurements in an inertial frame, the proposed robust noncooperative control schemes with input saturation constraint are easier to implement in practice. Finally, numerical simulations and SimMechanics experiments are provided to illustrate the effectiveness of the proposed theoretical results.