- Professor of Aerospace Engineering, Research interests: Aerospace Robotics, Guidance, Navigation and Controledit
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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Operation of mobile robots in off-road environment requires the attention to the torque saturation problem that occurs in the wheels DC motors while climbing hills. In the present work, off-road conditions are utilized to benefit while... more
Operation of mobile robots in off-road environment requires the attention to the torque saturation problem that occurs in the wheels DC motors while climbing hills. In the present work, off-road conditions are utilized to benefit while avoiding torque saturation. Energy optimization algorithm using predictive control is implemented on a two-DC motor-driven wheels mobile robot while crossing a ditch. The predictive control algorithm is simulated and compared with the PID control and the open-loop control. Predictive control showed more capability to avoid torque saturation and noticeable reduction in the energy consumption. Furthermore, using the wheels motors armature current instead of the supply voltage as control variable in the predictive control showed more efficient speed control. Simulation results showed that in case of known ditch dimensions ahead of time, the developed algorithm is feasible. Experimental examination of the developed energy optimization algorithm is presented. The experimental results showed a good agreement with the simulation results. The effects of the road slope and the prediction horizon length on the consumed energy are evaluated. The analytical study showed that the energy consumption is reduced by increasing the prediction horizon until it reaches a limit at which no more energy reduction is obtained. This limit is proportional to the width of the ditch in front of the mobile robot. Curve fitting is applied to the obtained results to address further the effect of the parameters on the energy consumption.
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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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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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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.
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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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This paper presents a new methodology to guide and control flexible wings UAV based on a stereo vision system with advanced fuzzy logic algorithms. This system allows to detect wing's deflections and shapes by using the novel... more
This paper presents a new methodology to guide and control flexible wings UAV based on a stereo vision system with advanced fuzzy logic algorithms. This system allows to detect wing's deflections and shapes by using the novel Deflection-Detection Vision System (DDVS). This methodology has three different steps. First, the shape of the wing was identified by the determinant the deflection points on the wing using the stereo camera. Second, the fuzzy logic algorithm was used to classify the shapes of the wing and to determine the flight parameters such as, speed, angle of attack and roll angle. Finally, an autopilot controller based on intelligent, Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm was designed. Extensive, experimental studies were performed in wind tunnel to determine the characteristics of the flexible wing. The testing were performed for wind speeds ranging from 11 to 31 km/h, angles of attack ranging from −20 deg to +20 deg. The experimental results were extended and verified with simulation experiments for wider ranges of velocities and angle of attack.
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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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The optimal performance of the conventional Kalman filters is not guaranteed, when there is uncertainty in the process and measurement noise covariances. In this paper, in order to reduce the effect of noise covariance uncertainty, the... more
The optimal performance of the conventional Kalman filters is not guaranteed, when there is uncertainty in the process and measurement noise covariances. In this paper, in order to reduce the effect of noise covariance uncertainty, the Fuzzy Adaptive Iterated Extended Kalman Filter (FAIEKF) and Fuzzy Adaptive Unscented Kalman Filter (FAUKF) are proposed to overcome this drawback. The proposed FAIEKF and FAUKF have been applied to fuse signals from Global Positioning System (GPS) and Inertial Navigation Systems (INS) for the autonomous vehicles’ navigation. In order to validate the accuracy and convergence of the proposed approaches, results obtained by FAUKF and FAIEKF were compared to the Fuzzy Adaptive Extended Kalman Filter (FAEKF), Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Iterated Extended Kalman Filter (IEKF). The simulation results illustrate the superior performance of the AKUKF compared to the other filters.
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This paper presents a novel approach to control of a flexible wing UAV using vision system. The aim of this paper is to develop a new technique to measure and classify the wing shape to control the airspeed, angle of attack (AOA), and the... more
This paper presents a novel approach to control of a flexible wing UAV using vision system. The aim of this paper is to develop a new technique to measure and classify the wing shape to control the airspeed, angle of attack (AOA), and the roll angle using a stereo camera. The deflection of the wing was extracted from experimental testing, and Fuzzy Logic was used to classify these shapes of the wing. Two different controllers were used: Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Linear Quadratic Regulator (LQR). The deflections of wing were measured for chosen locations of landmarks on a flexible wing using a stereo camera. The camera was placed at the rear end of the wing structure, and the entire wing was in the view. The stereo camera was used to study the characteristics of the flexible wings in wind tunnel testing at wind speeds ranging from 11 to 31 km/h, angles of attack ranging from −20 to 20 degree and roll angles ranging from −10 to 10 degree. In addition, fuzzy logic control was used to classify the shape of wing based on the deflection values. This algorithm determines the flight characteristics such as the airspeed, angle of attack and roll angle. Furthermore, two modules of a controller were designed for achieving the desired performance. Simulation and experiment results have been presented and verified.
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This paper compares two commonly used algorithms to solve Simultaneous Localization and Mapping (SLAM) problem in order to safely navigate an outdoor autonomous robot in an unknown location and without any access to a priori map. EKF-SLAM... more
This paper compares two commonly used algorithms to solve Simultaneous Localization and Mapping (SLAM) problem in order to safely navigate an outdoor autonomous robot in an unknown location and without any access to a priori map. EKF-SLAM is considered as a classical method to solve SLAM problem. This method, however, suffers from two major issues; the quadratic computational complexity and
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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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This paper proposes two methods to enhance traditional extended Kalman filter for UAV navigation. One is based on using fuzzy rules to choose parameters of an adaptive Kalman filter. The other uses inherent parallelism to speed up... more
This paper proposes two methods to enhance traditional extended Kalman filter for UAV navigation. One is based on using fuzzy rules to choose parameters of an adaptive Kalman filter. The other uses inherent parallelism to speed up iterations in Kalman filter computations. Both methods are described briefly and simulation results are presented.
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Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations needs to be built in the controllers of each... more
Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations needs to be built in the controllers of each autonomous robot. In this paper is investigated self-organizing formations control for material transfer, as an alternative to Automatic Guided Vehicles (AGVs). Leader-follower approach is applied for controllers design to drive the robots toward the goal. The results confirm the ability of velocity potential approach for motion control of both self-organizing formations.
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This paper presents a method which allows one to pass transversally through singularities of corank 1 for redundant manipulators. The method modifies a Jacobian matrix of the manipulator's forward kinematics to retrieve its full rank... more
This paper presents a method which allows one to pass transversally through singularities of corank 1 for redundant manipulators. The method modifies a Jacobian matrix of the manipulator's forward kinematics to retrieve its full rank at singularities. The method is computationally inexpensive and conceptually simple. It is well suited for real time control and practical implementations. The method is illustrated with the example of a 3-link planar pendulum.
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Navigation of autonomous vehicles and robots can be divided into two categories: indoor navigation and outdoor navigation. In general the outdoor navigation is more difficult and complex task because often the environment does not have... more
Navigation of autonomous vehicles and robots can be divided into two categories: indoor navigation and outdoor navigation. In general the outdoor navigation is more difficult and complex task because often the environment does not have characteristic points that can be identified and with respect to which robots could relate their position. If environment is unstructured (e.g. off-road environment), problems related to autonomous navigation are very difficult. Problems related to navigation in the unstructured environment could be divided into mapping, localization, collision avoidance and trajectory tracking.
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Autonomous navigation in an outdoor environment can be effectively performed by small robots but remains a challenging task as soon as real scale ground vehicles are concerned. An intelligent mobile robot which uses a real armor ground... more
Autonomous navigation in an outdoor environment can be effectively performed by small robots but remains a challenging task as soon as real scale ground vehicles are concerned. An intelligent mobile robot which uses a real armor ground vehicle as a platform is currently being developed for security applications (Fig. 30.1(a)). The robot tasks needed to be addressed are patrolling, surveillance,
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ABSTRACT Vehicle path tracking control problem is investigated using optimal control technique. Steering angle is subject to two limitations - both its magnitude and rate are bounded. Although, it is the most natural settings from the... more
ABSTRACT Vehicle path tracking control problem is investigated using optimal control technique. Steering angle is subject to two limitations - both its magnitude and rate are bounded. Although, it is the most natural settings from the application point of view - it has been rarely considered. An approach described in this paper utilizes the shortest-time solution for a 3-rd order linear system known for long time and revisited in the nineties to improve its robustness. Main generalization proposed here concerns state limitations resulting from the bounds over steering magnitude. Linear settings is sufficient if the offsets from the desired path are small. The validity of the ”linear”' solution is verified by applying the obtained optimal bang-bang control to a nonlinear system. In case of large lateral and angular offsets from the path the nonlinear analysis is needed. We show that in spite of the low dimension of the system (third) the nonlinear problem presents a variety of challenges, namely, singular optimal trajectory and a Fuller-type phenomena consisting of 'chattering' near the junction of non-singular and singular portions of optimal trajectories. Finally, the controller designed using linear technique is tested with nonlinear model in simulation and experimentally.
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Mobile robot motion control with collision avoidance is investigated in this paper for the case of unknown obstacles which are locally sensed. Motion control achieves in this case a reactive motion using velocity potential fields approach... more
Mobile robot motion control with collision avoidance is investigated in this paper for the case of unknown obstacles which are locally sensed. Motion control achieves in this case a reactive motion using velocity potential fields approach in a modified, quasi-harmonic, solution. Analytical solutions and simulations show how the harmonic solution for collision avoidance can be separated smoothly from a non-harmonic solution for positioning at a fixed goal.
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ABSTRACT
Research Interests: Engineering, Newtonian Dynamics, Model Predictive Control, Motion control, Aerodynamics, and 15 morePath planning, Navigation, Mobile Robots, Robot kinematics, Remotely Operated Vehicles, Predictive models, Autonomous Vehicle, Three Dimensional, Path Planning, Dynamic Model of WSN, Input Output, Model Based Predictive Control, Predictive Control, dynamic model, and Inclined plane
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