- Professor of Aerospace Engineeringedit
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Thin plate surface temperature control is investigated using inverse problem in a closed loop control approach. This was achieved by solving the periodic boundary one-dimensional heat conduction equation, using Laplace transform, to get... more
Thin plate surface temperature control is investigated using inverse problem in a closed loop control approach. This was achieved by solving the periodic boundary one-dimensional heat conduction equation, using Laplace transform, to get the transfer function for both direct problem and inverse problem. The resulting transfer functions were processed using Zero-Pole expansion to get a polynomial transfer functions for facilitating the simulation. After the simulation study of the closed loop temperature control, a closed loop experimental approach was developed using the inverse problem from simulation and connecting the results with a physical system by replacing the simulated direct problem. Experimental results were compared to previous simulation results.
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Through the use of telerobotics, surgeons can perform operations on patients from a distance, via a communication network. However, a major issue to these procedures is the existence and effect of time delays, which are known to... more
Through the use of telerobotics, surgeons can perform operations on patients from a distance, via a communication network. However, a major issue to these procedures is the existence and effect of time delays, which are known to negatively affect performance. In addition, the forces that occur due to tool-tissue interaction may also present problems during operations. This paper investigates and compares the use of Proportional-Integral-Derivative (PID) controllers and Model Predictive Controllers (MPCs) used in hybrid control, and their effects on the performance of the da Vinci™Patient Side Manipulator (PSM), a surgical robot, when subjected to different time delays. It was found that hybrid MPCs have better trajectory control, however hybrid PID controllers exhibit greater ability to adapt to undesirable external forces from contact. Further research into implementing a predictor with the PID controllers and comparing results, as well as integrating benefits of both controllers into a single hybrid control would provide great benefits for improving surgical telerobotic performance.
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ABSTRACT Remote multisensing problem results from the use a variety of instruments in non-collocated measurement of time varying quantities. Variables measured by multiple sensors h ave to b e associated with spatial coordinates and... more
ABSTRACT Remote multisensing problem results from the use a variety of instruments in non-collocated measurement of time varying quantities. Variables measured by multiple sensors h ave to b e associated with spatial coordinates and synchronized in time. Sensors outputs are, however, dependent not only on the inputs from measured variables, but also by the instrument inner dynamics. Sensor fusion is accurate only if it uses signals with properly calibrated magnitudes and with the same phase shifts. An effective approach for achieving these requirements is dynamic calibration of individual sensors output signals. This paper investigates dynamic calibration as an inverse problem and proposes to use the solutions developed for such problems. Numerical results illustrate the benefits of dynamic calibration for remote sensing.
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ABSTRACT This paper presents a modified version of HybridSLAM (HS) method using unscented Kalman filter to solve simultaneous localization and mapping problem. Instead of applying extended Kalman filter for SLAM (EKF-SLAM) to build the... more
ABSTRACT This paper presents a modified version of HybridSLAM (HS) method using unscented Kalman filter to solve simultaneous localization and mapping problem. Instead of applying extended Kalman filter for SLAM (EKF-SLAM) to build the map of the environment, an unscented Kalman filter (UKF) was added to the HS algorithm. This would allow including higher order of non-linearity of the motion. The new method called Unscented HybridSLAM (UHS) is constructing the global map more accurately compare to the original HS and by employing the same constraint of local sub-map fusion technique, a more reliable solution to SLAM problem is achieved. The unscented Kalman filter takes advantage of both statistical and analytical linearization techniques to estimate the global map. The local map in the vicinity of the robot is estimated using FastSLAM and the local map is fused to the map using constrained local sub-map fusion technique. Unscented HybridSLAM uses a minimal set of chosen samples to approximate the posterior mean and covariance for a nonlinear system. The unscented HybridSLAM performance is compared to the original HybridSLAM and FastSLAM algorithms and it is shown that in case of severe nonlinearity, the proposed unscented HybridSLAM is outperforming current filters in terms of estimation of the path and map building.
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Space Robotics is a relatively new field of science and engineering that was developed as an answer to growing needs created by space exploration and space missions. New technologies had to be invented and designed in order to meet... more
Space Robotics is a relatively new field of science and engineering that was developed as an answer to growing needs created by space exploration and space missions. New technologies had to be invented and designed in order to meet demands in extremely hostile environments. Those technologies have to work in a gravityless environment, rarefied atmosphere and often in high temperature. This paper recalls some of the major robotics missions in space and explains technologies related to them. Space robotic manipulators, especially flexible link and flexible joint robots are discussed. Autonomous robots for unmanned, long duration mission are presented.
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The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference... more
The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2014 received 301 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, 20% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of ICINCO 2014. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.
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A Fuzzy Logic Adaptive Control (FLAC) is used to adjust the exponential weighting parameter of a weighted Error-State Kalman Filter (ESKF) in an INS/GNSS system. The FLAC is used to prevent the Kalman Filter (KF) from diverging or to... more
A Fuzzy Logic Adaptive Control (FLAC) is used to adjust the exponential weighting parameter of a weighted Error-State Kalman Filter (ESKF) in an INS/GNSS system. The FLAC is used to prevent the Kalman Filter (KF) from diverging or to reach to a high bound when the IMU produces colored noise. Furthermore, a matrix notation for the weighting parameter alpha is introduced and compared against the single alpha value. First, the results show the influence of a colored noise in the system, which makes the ESKF reaching a large error bound solution. The application of FLAC considering both constant and matrix alpha reduces the error boundary for the position and velocity states. However, the constant alpha leads to an inaccurate altitude, bias correction, and error covariance matrix. The matrix alpha parameter shows a final solution that improves the navigation accuracy for all states, preserving the stability of the error covariance matrix.
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The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference... more
The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2014 received 301 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, 20% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of ICINCO 2014. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.
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Robots mounted on an unmanned chaser satellite could be used for performing rendezvous and grasping manoeuvres in order to repair satellites or remove space debris from orbit. Use of manipulators for such purposes is challenging, since... more
Robots mounted on an unmanned chaser satellite could be used for performing rendezvous and grasping manoeuvres in order to repair satellites or remove space debris from orbit. Use of manipulators for such purposes is challenging, since the performed task need to be done autonomously, accurately and with high level of robustness. During manoeuvres high disturbances might appear e.g. due to contact between the manipulator arm end-effector and the target spacecraft. In this paper an approach for validation of the robotic subsystem during chaser rendezvous and grasping manoeuvre has been shown. Two type of testbed systems were used: planar air-bearing microgravity simulators and a test-bed system with industrial robots. The proposed approach took advantage of possible replacement of particular subsystem in reference model or reference hardware in specified test-bed system. The list of tests performed are included in the paper.
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The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference... more
The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2014 received 301 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, 20% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of ICINCO 2014. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.
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In this paper the energy efficient Newton algorithm applied to nonholonomic motion planning is presented. The energy optimization is performed by coupling motion in the null space of the Jacobian matrix derived from the nonholonomic... more
In this paper the energy efficient Newton algorithm applied to nonholonomic motion planning is presented. The energy optimization is performed by coupling motion in the null space of the Jacobian matrix derived from the nonholonomic system, which gives the energetic efficiency, and the motion towards the goal, saving the convergence property. Resulting controls are smooth and easy to generate for motors or thrusters. The method can be used to steer free-floating objects as well as mobile robots.
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Most advanced trajectory tracking control laws for robot manipulators require a knowledge of all state variables. For lightweight flexible-joint space manipulators this objective is difficult to achieve since link positions are typically... more
Most advanced trajectory tracking control laws for robot manipulators require a knowledge of all state variables. For lightweight flexible-joint space manipulators this objective is difficult to achieve since link positions are typically not measured. In this paper, an extended Kalman filter (EKF) observer to estimate all state variables of a manipulator system modeled with a nonlinear stiffness dynamics model is presented. In addition, it is shown that the observer can be modified in order to calibrate in real-time the sensor biases. The state variable estimates are coupled to a flexible joint adaptive controller to provide a complete closed-loop trajectory tracking solution. Simulation results show that the proposed solution provides satisfying tracking performance in a 12.6 ×12.6 m trajectory tracking scenario.
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This paper examines the effect on achievable depth accuracy of a stereo vision system as the baseline between the two camera sensors changes. This is critical for Unmanned Aerial Vehicle navigation or UAV aerial refueling, and for space... more
This paper examines the effect on achievable depth accuracy of a stereo vision system as the baseline between the two camera sensors changes. This is critical for Unmanned Aerial Vehicle navigation or UAV aerial refueling, and for space debris clearance operations. The theory behind stereo image depth calculation is explained and then synthetic pixel data is manufactured in order to determine a 95% confidence interval on depth under two camera baseline conditions. A Gaussian pixel error is add to simulate Harris corner detection error. A disparity of the order of 10 pixels or less produces more than 1 cm difference between expected and actual depth for the stereo camera bases examined. For a 1-pixel disparity the difference is of the order of 50%. Future research is discussed.
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In the paper a linear quadratic Gaussian (LQG) dynamic regulator is applied with an extended Kalman filter (EKF), a LQG with fuzzy logic adaptive EKF (FLAEKF), LQG with an EKF and a FLAEKF combined with time delays in the feedback loop... more
In the paper a linear quadratic Gaussian (LQG) dynamic regulator is applied with an extended Kalman filter (EKF), a LQG with fuzzy logic adaptive EKF (FLAEKF), LQG with an EKF and a FLAEKF combined with time delays in the feedback loop for modeling non-minimum phase (NMP) response for control of the end effector with non-collocated sensor and in the feed-forward loop for corrective control of a two-link flexible robot in the tracking of square trajectory task. The system is compared in simulations with a fuzzy logic system (FLS) vibration suppression control system. Results show that FLS adaptive vibration suppression yields higher tracking precision than FLAEKF, EKF or corrective time delays. It is also more effective while maintaining tracking accuracy and reasonable time efficiency than the classical PID controller or advanced adaptive controllers. Recursive nonparametric identification procedure for nonlinear friction in the joints of flexible robot is introduced. Its asymptotic properties are investigated.
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In this paper an advanced control system for an elastic joint two-link flexible link robot manipulator is considered. The system uses controller with an adaptive fuzzy logic. Nonlinear friction in the joints is modeled by the Hammerstein... more
In this paper an advanced control system for an elastic joint two-link flexible link robot manipulator is considered. The system uses controller with an adaptive fuzzy logic. Nonlinear friction in the joints is modeled by the Hammerstein system. It is identified by the algorithm based on nonparametric nearest neighbor regression estimation. The asymptotically optimal choice of the parameters of the algorithm are investigated.
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The paper compares control strategies for four flexible space robot manipulators including the classical Slotine and Li algorithm, a simple proportional derivative controller, a singular perturbation-based controller and a nonlinear... more
The paper compares control strategies for four flexible space robot manipulators including the classical Slotine and Li algorithm, a simple proportional derivative controller, a singular perturbation-based controller and a nonlinear backstepping controller. All strategies are tested and compared in simulations involving endpoint target positioning while tracking a square trajectory by a two-link flexible joint space robot. Simulation results indicate that controlling both nonlinearities and joint flexibility effects improve the closed-loop behavior of the space robot where the control of nonlinearities is of greater importance. The best performance is achieved by the nonlinear backstepping control strategy. We also propose Hammerstein nonlinear joint model and introduce its nonparametric nearest neighbor kernel identification algorithm and study its convergence.
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The optimal performance of the Kalman filters is highly dependent on the measurement and process noise characteristics, making the whole system unable to achieve the desired estimation in the presence of non-Gaussian mean noise... more
The optimal performance of the Kalman filters is highly dependent on the measurement and process noise characteristics, making the whole system unable to achieve the desired estimation in the presence of non-Gaussian mean noise distribution and high initial uncertainties. Recently, the H-infinity filter, as a robust algorithm, has been broadly used, as it is not being dependent on the pre-knowledge of the noise nature; however, making a balance between high robustness and estimation accuracy is a challenging issue. Hence, to overcome this problem, a new adaptive H-infinity extended Kalman filter (AHEKF) was designed in this paper, which benefits from both high robustness and precision. The suggested algorithm contains two adaptive sections to achieve high accuracy as well as controlling the effects of time-varying noise characteristics, high initial uncertainties, and abnormal data that can degrade the accuracy of state estimation in an integrated navigation system. The presented al...
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This paper presents navigation and control of a robot for capturing a moving target using the vision system. A stereo camera is used to calculate the pose of the moving target (position and orientation). An Adaptive Unscented Kalman... more
This paper presents navigation and control of a robot for capturing a moving target using the vision system. A stereo camera is used to calculate the pose of the moving target (position and orientation). An Adaptive Unscented Kalman Filter (AUKF) is used to generate an optimal path to capture the moving object by estimating the state vector (position, orientation, linear and angular velocities) of the target. The Fuzzy Logic Adaptive System (FLAS) has been used to prevent the AUKF from divergence. The FLAS can evaluate the performance of UKF and tuning the factors in the weighted covariance to improve the accuracy of UKF. A new trajectory planning method for the space robot is proposed based on the information acquired from the vision system and estimation the linear and angular velocities of the target by AUKF. The results from simulation experiments were presented and discussed. It was concluded that the Fuzzy Adaptive Unscented Kalman Filter methods give more accurate results rather than the Unscented Kalman filter or Extended Kalman Filter.
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This paper present and discusses algorithms suitable for visual navigation for mobile and flying robots. Three different algorithms were used to explore the direct method for the vision system. Those methods are Homography, Iterative... more
This paper present and discusses algorithms suitable for visual navigation for mobile and flying robots. Three different algorithms were used to explore the direct method for the vision system. Those methods are Homography, Iterative Closest Point (ICP), and Horn’s Absolute Orientation. Those algorithms were tested on the camera with moving baseline. The relations between optimal baseline and depth distance were discussed. The camera’s calibration process has been presented and discussed. Several experiments with the different image noise level were performed. The noise levels influence on distance and pose estimation accuracy were discussed. Measurements and estimation errors for both mobile and flying robots were shown and compared with different methods.