Motion blur compensated optical pose estimation for non-cooperative space targets using adaptive multi-scale ellipse fitting

We have investigated the use of forward looking infrared (FLIR) sensors to verify aircraft navigation information during approach and landing. Our research includes the development of an experimental primary flight display (PFD) integrated with a synthetic vision system (SVS). The effectiveness of a traditional SV display is limited by navigation equipment position and orientation errors, database limitations, and lack of knowledge of temporary obstacles. However, integrating information from the navigation system with an external FLIR sensor has the potential to increase information provided to the pilot, improving flight safety. In prior work, we developed software to correct aircraft orientation inaccuracies. Our algorithm locates the runway in a LWIR image and uses the extracted runway location to validate and correct the SV system's understanding of aircraft orientation. Evaluations demonstrated that this orientation correction worked well when there were no position errors. However, uncorrected position inaccuracies introduce errors into the pitch and heading correction estimates as the aircraft approaches the runway. To address this problem, we have developed a new algorithm to separate the image effects of orientation and position errors. This allows our system to correct for both orientation and position errors. We evaluated our system using LWIR video and navigation data recorded by test aircraft during runway approaches. Our results show significant improvements in correction accuracy using dual orientation and position estimation compared to orientation correction alone.

A unified model is proposed for the output accuracy of open-chain manipulators in consideration of joint clearance and structural parameters. First, the operator of the finite-displacement screw matrix and the combination operation are presented. Second, the joint clearance and structural parameters are described and analyzed with screw theory. A virtual screw is established for the joint clearance and structural parameter errors. Third, a unified model is built through the adjoint transformation of Lie groups in consideration of the two effectors of the virtual screw. The error pose is decomposed into orientation and position errors, which are obtained through the virtual screw. Finally, an open-chain manipulator with six degrees of freedom is analyzed based on the proposed model. The position and orientation errors are obtained with the trajectory that provided an intuitive geometric insight into the accuracy and exact maximal position and orientation errors.

This paper presents an improved methodology for evaluating the position and orientation errors of airfoil sections of a manufactured aero-engine blade. The existing method estimates these errors by finding rigid-body transformations with translational and rotational parameters altogether to best match the inspection data points onto the design airfoil profiles. Such transformations lead to unreliable evaluation results due to combining the position and orientation errors with each other. This paper proposes to decouple the position and orientation errors in their evaluation in order to avoid the combining effect. To isolate the position error from the orientation error, an important location tolerance evaluation feature, the centroid of a manufactured airfoil section, must be correctly identified from the sectional inspection data points. Identifying the centroid location directly from discrete data points is subject to an error caused by biased area calculations on the pressure and suction sides of an airfoil. This work proposes to reconstruct a valid airfoil profile from the inspection data points for each airfoil section to overcome the area bias problem and to maintain consistency in identifying the centroid. With the centroid of each inspected airfoil section identified, the position error and the orientation error can then be evaluated in sequence. A series of case studies has been performed to demonstrate the effectiveness of the proposed methodology and how it is able to prevent wrongful rejection/acceptance of geometrically acceptable/unacceptable blades as well as incorrect modification of the related manufacturing processes.

A novel modified firefly algorithm (MFA) for optimal and accurate robotic trajectory planning has been proposed in this paper. In order to demonstrate the entire trajectory planning problem, an industrial 4-DOF SCARA robot manipulator has been chosen. An error function which is a combination of both error in position and error in orientation coordinates is defined as total objective function for the trajectory optimization assignment. In order to accomplish an efficient optimal trajectory, the best cost of the error objective fitness function, algorithm convergence speed, the error in positions and orientations are chosen as performance parameters. The objective function has been executed using bat algorithm (BA), cuckoo-search algorithm (CS), firefly algorithm (FA), artificial bee colony (ABC) algorithm and the proposed MFA. The effectiveness of the proposed MFA is validated by carrying out a comparative review of the acquired trajectory results from the MFA against the other considered existing algorithms. The ranks of the algorithms have been evaluated by conducting Friedman test for the mean solutions of error in positions and orientation. The comparative study of the implemented algorithms shows that MFA executes superior to the other algorithms with less computational effort for the same boundary conditions.

We present a novel algorithm to remove motion blur from a single blurred image. To estimate the unknown motion blur kernel as accurately as possible, we propose an adaptive algorithm using aniso- tropic regularization. The proposed algorithm preserves the point spread function PSF path while keeping the properties of the motion PSF when solving for the blur kernel. Adaptive anisotropic regularization and refine- ment of the blur kernels are incorporated into an iterative process to improve the precision of the blur kernel. Maximum likelihood ML esti- mation deblurring based on edge-preserving regularization is derived to reduce artifacts while avoiding oversmoothing of the details. By using the estimated blur kernel and the proposed ML estimation deblurring, the motion blur can be removed effectively. The experimental results for real motion blurred images show that the proposed algorithm can removes

There is increased interest in networking arrays of sensors for distributed source localization. An analysis of the generalized model and estimation performance for multiple sources being observed by a field of networked arrays has recently been studied in via the Cramer-Rao lower bound (CRLB). In previous work concerning the CRB and multiple sources, the models were formulated for observations with a distributed network of sensor arrays. However, previous work assumed completely known sensor orientation and position. In real world systems such as distributed sonar systems, this is rarely the case. In this paper, sensor orientation and position errors are incorporated into the signal model. Simulation examples are given that show that a network of a high number of low-complexity arrays outperforms a network of a low number of high resolution arrays when considering subarray position and orientation errors. This occurs even though the high resolution array network has four times as many sensing elements.

In order to evaluate the weapon strike effect in the joint of ship formation, this paper discusses the influence of platform positioning and orientation error on weapon strike effect. Based on the mathematical model, the damage expectation of platform positioning and orientation error, the long-range strike accuracy of shipboard missile and the target indicating accuracy of cross-platform are analyzed quantitatively. The model includes weapon strike likelihood, the navigation positioning error model and error transfer model of ship platform. The simulation was be perform in MATLAB environment. The larger the positioning and orientation error is, the more cross platform target sign error will increase. And the acquisition probability and weapon strike effect of missile long-range attack will reduce.

A wheeled train uncoupling robot with four degrees-of-freedom has been developed to replace humans in the uncoupling task in a marshalling field for designating freight cars to different destinations. To successfully achieve the task in practical applications, the positioning accuracy of the robot is an important issue to be considered. Based on the kinematic model using Denavit–Hartenberg method, the matrix differential method is applied here to establish the static position and orientation error model. The impact of parameter errors upon the static pose error of the uncoupling manipulator is analysed. The flexibility of the robot's key components is taken into consideration to analyse its impact on the position and orientation error of the manipulator. The position and orientation error compensation is developed by using input motion planning method to improve the pose accuracy of the robot. Additional motions are added to each joint of the robot such that the uncoupling manipulator can generate a corresponding tiny perturbation, which is used to eliminate the positioning error, ensuring the uncoupling action is completed successfully.

On orbit capture is an essential technical for space debris removal, refueling or malfunction satellite repairing. While due to the uncertainty of non-cooperative targets, the impact between the manipulator and the space non-cooperative target is inevitable. It may alter the position and the attitude of the spacecraft’s base, and cause the on-orbit tasks fail, and the energy of the impact/vibration is dissipated. In this paper, a novel approach is proposed for impact/vibration control and energy management in the process of non-cooperative space target capture. In which, a passive energy harvesting device, which is installed between the satellite and the capture device, is design to harvest the energy of the impact/vibration in the space target capture. In the capture process, the impact/vibration perturbation is reduced by nonlinear damping and friction of the isolation device, and the energy of which is harvested. The dynamic equation of the energy harvesting system is provided, and a sliding control approach is developed to stable the impact/vibration perturbation. Then a novel energy management for the impact perturbation control of the capture process is proposed, in which the total energy consumption is defined as the control energy consumption minus the harvested energy. The control time is regarded as a free variable to optimize and minimized the total energy consumption is the optimization target. This work provides a useful method for the passive suppression system design and optimization for the perturbation control of the non-cooperative spacecraft capture.

Accurate and robust estimates of camera position and orientation in a bronchoscope are required for navigation. Fusion of pre-interventional information (e.g., CT, MRI, or US) and intra-interventional information (e.g., bronchoscopic video) were incorporated into a navigation system to provide physicians with an augmented reality environment for bronchoscopic interventions. Two approaches were used to predict bronchoscope movements by incorporating sequential Monte Carlo (SMC) simulation including (1) image-based tracking techniques and (2) electromagnetic tracking (EMT) methods. SMC simulation was introduced to model ambiguities or uncertainties that occurred in image- and EMT-based bronchoscope tracking. Scale invariant feature transform (SIFT) features were employed to overcome the limitations of image-based motion tracking methods. Validation was performed on five phantom and ten human case datasets acquired in the supine position. For dynamic phantom validation, the EMT-SMC simulation method improved the tracking performance of the successfully registered bronchoscopic video frames by 12.7% compared with a hybrid-based method. In comparisons between tracking results and ground truth, the accuracy of the EMT-SMC simulation method was 1.51 mm (positional error) and 5.44° (orientation error). During patient assessment, the SIFT-SMC simulation scheme was more stable or robust than a previous image-based approach for bronchoscope motion estimation, showing 23.6% improvement of successfully tracked frames. Comparing the estimates of our method to ground truth, the position and orientation errors are 3.72 mm and 10.2°, while those of our previous image-based method were at least 7.77 mm and 19.3°. The computational times of our EMT- and SIFT-SMC simulation methods were 0.9 and 1.2 s per frame, respectively. The SMC simulation method was developed to model ambiguities that occur in bronchoscope tracking. This method more stably and accurately predicts the bronchoscope camera position and orientation parameters, reducing uncertainties due to problematic bronchoscopic video frames and airway deformation during intra-bronchoscopy navigation.

The paper describes a new method to reduce the positioning error of 3-degree-of-freedom (3Dof) mobile robots. The 3Dof robot uses 3 omni-wheels as the motion system. A combination of a modified odometry system and a vision-based self-localization algorithm and a two-channel complementary filtering algorithm is used. The low frequency stability of the vision sensors with the high frequency tracking of the odometry sensor leads us to achieve both dynamic and static stability of positioning. Two new algorithms are introduced in order to calculate the position and orientation of the robot using the results from the odometry sensors. An omni-directional camera provides vision data for the self-localization algorithm, which calculates the robot position according to the angles under which the known obstacles around the robot are viewed. In order to check the improvement of the proposed positioning system compared to existing systems, a test condition is suggested to measure the position and orientation errors. The results of this test show that an improvement of 80% in position error and 86% in orientation error is achieved.

The performance of automatic guided vehicles (AGVs) is gauged by their position and orientation errors. Sometimes the orientation errors are not measurable, and output feedback using position errors only is employed. In this paper, a controller using output feedback is proposed for a differential-wheel-drive AGV with a simple linear array of 64/spl times/1 opto-sensors. A linear controller is first developed. The performance of the linear controller is further improved using fuzzy logic. Two fuzzy-logic controllers are accordingly formed. Stability based on the Hurwitz criterion, the Popov criterion, and the phase-plane method is demonstrated. Experimental results using a laboratory AGV are provided to illustrate the effectiveness of the proposed controllers.

To estimate influence of velocity on kinematic accuracy for a cross-linked Stewart type Parallel Machine Tool, position and orientation errors of the moving tool platform are researched. Based on rigid body dynamics, inertial and friction forces and moments are considered. Firstly, analytical expression of driving force is derived for each link. Secondly, change of length is derived using Hooke’s Law for each link. Then mapping matrix between change of link length and change of platform position and orientation is derived based on both Euler angle and revolving angle around a spatial axis. Finally, analytical expression of position and orientation errors of the moving platform is derived. Figures of distribution of position and orientation errors in workspace under two velocities are obtained respectively. The results show that, in frequently used workspace, all of the three components of position error are less than 3.5μm. All of them increase with z coordinate of platform center. Position error is influenced slightly by velocity. The difference of position error between two velocities is less than 2%.

Although capsule endoscopy is already used for diagnosis of the gastrointestinal tract, a method to precisely localize the capsules, important for accurate diagnosis, is lacking. Static magnetic localization is a promising solution for that purpose. In this paper, the simulation of a differential static magnetic localization system with dynamic geomagnetic compensation was optimized. First, a convergence-test for the position and orientation errors as a function of the dimension of the computational domain was conducted. Subsequently, the diameter-to-length ratio of a permanent magnet was varied and the corresponding position and orientation errors, as well as the mean magnetic flux density measured at the sensor positions, were compared. The results revealed that for a computational domain radius of 800 mm, the position and orientation errors converged to less than 0.1 mm and 0.1°, respectively. The position and orientation errors were also of that order, even with the smallest permanent magnet employed in the study. Furthermore, the mean magnetic flux density measured at the sensors of the proposed magnetic localization system would be detectable using state-of-the-art magnetometers. It is concluded that the differential localization method is also feasible for small permanent magnets, which is especially important considering the limited space within endoscopy capsules.

Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines.