Nuno Filipe

Adaptive Position and Attitude Tracking Controller for Satellite Proximity Operations using Dual Quaternions

This paper proposes a nonlinear adaptive position and attitude-tracking controller for satellite proximity operations between a target and a chaser satellite. The controller requires no information about the mass and inertia matrix of the chaser satellite and takes into account the gravitational acceleration, the gravity-gradient torque, the perturbing acceleration due to Earth’s oblateness, and constant (but otherwise unknown) disturbance forces and torques. Sufficient conditions to identify the mass and inertia matrix of the chaser satellite are also given. The controller is shown to ensure almost global asymptotical stability of the translational and rotational position and velocity tracking errors. Unit dual quaternions are used to simultaneously represent the absolute and relative attitude and position of the target and chaser satellites. The analogies between quaternions and dual quaternions are explored in the development of the controller.

Extended Kalman Filter for Spacecraft Pose Estimation Using Dual Quaternions

Based on the highly successful quaternion multiplicative extended Kalman filter for spacecraft attitude estimation using unit quaternions, this paper proposes a dual quaternion multiplicative extended Kalman filter for spacecraft pose (i.e., attitude and position) and linear and angular velocity estimation using unit dual quaternions. By using the concept of error unit dual quaternion, defined analogously to the concept of error unit quaternion in the quaternion multiplicative extended Kalman filter, this paper proposes, as far as the authors know, the first multiplicative extended Kalman filter for pose estimation. The state estimate of the dual quaternion multiplicative extended Kalman filter can directly be used by recently proposed pose controllers based on dual quaternions, without any additional conversions, thus providing an elegant solution to the output dynamic compensation problem of the full six degree-of-freedom motion of a rigid body. Three formulations of the dual quaternion multiplicative e...

Simultaneous position and attitude control without linear and angular velocity feedback using dual quaternions

In this paper, we suggest a new representation for the combined translational and rotational dynamic equations of motion of a rigid body in terms of dual quaternions. We show that with this representation it is relatively straightforward to extend existing attitude controllers based on quaternions to combined position and attitude controllers based on dual quaternions. We show this by developing setpoint nonlinear controllers for the position and attitude of a rigid body with and without linear and angular velocity feedback based on existing attitude-only controllers with and without angular velocity feedback. The combined position and attitude velocity-free controller exploits the passivity of the rigid body dynamics and can be used when no linear and angular velocity measurements are available.

Adaptive Model-Independent Tracking of Rigid Body Position and Attitude Motion with Mass and Inertia Matrix Identification using Dual Quaternions

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Cooperative Relative Navigation for Space Rendezvous and Proximity Operations using Controlled Active Vision

This work aims to solve the problem of relative navigation for space rendezvous and proximity operations using a monocular camera in a numerically efficient manner. It is assumed that the target spacecraft has a special pattern to aid the task of relative pose estimation, and that the chaser spacecraft uses a monocular camera as the primary visual sensor. In this sense, the problem falls under the category of cooperative relative navigation in orbit. While existing systems for cooperative localization with fiducial markers allow full six-degrees-of-freedom pose estimation, the majority of them are not suitable for in-space cooperative navigation especially when involving a small-size chaser spacecraft, due to their computational cost. Moreover, most existing fiducial-based localization methods are designed for ground-based applications with limited range e.g., ground robotics, augmented reality, and their performance deteriorates under large-scale changes, such as those encountered in space applications. Using an adaptive visual algorithm, we propose an accurate and numerically efficient approach for real-time vision-based relative navigation, especially designed for space robotics applications. The proposed method achieves low computational cost and high accuracy and robustness via the following innovations: first, an adaptive visual pattern detection scheme based on the estimated relative pose is proposed, which improves both the efficiency of detection and the accuracy of pose estimates; second, a parametric blob detector called Box-LoG is used, which is computationally efficient; and third, a fast and robust algorithm is introduced, which jointly solves the data association and pose estimation problems. In addition to having an accuracy comparable to state-of-the-art cooperative localization algorithms, our method demonstrates a significant improvement in speed and robustness for scenarios with large range changes. A vision-based closed-loop experiment using the Autonomous Spacecraft Testing of Robotic Operations in Space ASTROS testbed demonstrates the performance benefits of the proposed approach.

Pose tracking without linearand angular-velocity feedback using dual quaternions

Since vision-based sensors typically cannot directly measure the relative linear and angular velocities between two spacecraft, it is useful to develop attitude- and position-tracking controllers- namely, pose-tracking controllers-that do not require such measurements. Using dual quaternions and based on an existing attitude-only tracking controller, a pose-tracking controller that does not require relative linear- or angular-velocity measurements is developed in this paper. Compared to the existing literature, this velocity-free pose-tracking controller guarantees that the pose of the chaser spacecraft will converge to the desired pose independent of the initial state, even if the reference motion is not sufficiently exciting. In addition, the convergence region does not depend on the gains chosen by the user. The velocity-free controller is verified and compared with a velocity-feedback controller through two simulations. In particular, the proposed velocity-free controller is compared qualitatively and quantitatively with a velocity-feedback controller and an extended Kalman filter using a relatively realistic satellite proximity-operation scenario.

Extended Kalman Filter for spacecraft pose estimation using dual quaternions

Based on the highly successful Quaternion Multiplicative Extended Kalman Filter (Q-MEKF) for spacecraft attitude estimation using unit quaternions, this paper proposes a Dual Quaternion Multiplicative Extended Kalman Filter (DQ-MEKF) for spacecraft pose (i.e., attitude and position) and linear and angular velocity estimation using unit dual quaternions. By using the concept of error unit dual quaternion, defined analogously to the concept of error unit quaternion in the Q-MEKF, this paper proposes, as far as the authors know, the first multiplicative EKF for pose estimation. Compared to existing literature, the state of the DQ-MEKF only includes six elements of a unit dual quaternion, instead of eight, resulting in obvious computational savings. A version of the DQ-MEKF is presented that takes only discrete-time pose measurements with noise and, hence, is suitable for uncooperative satellite proximity operation scenarios where the chaser satellite has only access to measurements of the relative pose, but requires the relative velocities for control. Finally, the DQ-MEKF is experimentally validated and compared with two alternative EKF formulations on a 5-DOF air-bearing platform.

Pose-Tracking Controller for Satellites with Time-Varying Inertia

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Applying Problem-Based Learning to instruction of system dynamics and controls

Problem-Based Learning is a pedagogy emphasizing student learning via solving authentic, difficult problems in teams. This paper describes the application of Problem-Based Learning in a large system dynamics and controls course for third-year undergraduate students in aerospace engineering at the Georgia Institute of Technology. The pros and cons of applying Problem-Based Learning to the teaching of controls are reviewed. The course design and implementation are described. Student opinions and grades (in this course and subsequent courses) are analyzed. The paper concludes with a discussion of lessons learned and recommendations for the application of problem-based learning.