Person:
Tsiotras, Panagiotis

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    Pose-Tracking Controller for Satellites with Time-Varying Inertia
    (Georgia Institute of Technology, 2014-08) Filipe, Nuno ; Holzinger, Marcus J. ; Tsiotras, Panagiotis
    Satellite proximity operations have been identified by NASA and the USAF as a crucial technology that could enable a series of new missions in space. Such missions would require a satellite to simultaneously and accurately track time-varying relative position and attitude profiles. Moreover, the mass and moment of inertia of a satellite are also typically time- varying, which makes this problem even more challenging. Based on recent results in dual quaternions, a nonlinear adaptive position and attitude tracking controller for satellites with unknown and time-varying mass and inertia matrix is proposed. Dual quaternions are used to represent jointly the position and attitude of the satellite. The controller is shown to ensure almost global asymptotic stability of the combined translational and rotational position and velocity tracking errors. Moreover, sufficient conditions on the reference motion are provided that guarantee mass and inertia matrix identification. The controller compensates for the gravity force, the gravity-gradient torque, Earth's oblateness, and unknown constant disturbance forces and torques. The proposed controller is especially suited for satellites with relatively high and quick variations of mass and moment of inertia, such as highly maneuverable small satellites equipped with relatively powerful thrusters and control moment gyros.
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    Robust Feature Detection Acquisition Tracking for Relative Navigation in Space with a Known Target
    (Georgia Institute of Technology, 2013-08) Cho, Dae-Min ; Tsiotras, Panagiotis ; Zhang, Guangeong ; Holzinger, Marcus J.
    Recent advances in robotics and computer vision have enabled the implementation of sophisticated vision-based relative navigation algorithms for robotic spacecraft using a single calibrated monocular camera. These techniques, initially developed for ground robots, show great promise for robotic spacecraft applications. However, several challenges still exist, which hinder the direct use of these approaches in the space environment without further modifications. For example, the use of a monocular camera for robotic spacecraft operations with respect to a known target configuration may be limited owing to the abrupt illumination changes in a low-Earth orbit, long duration target tracking requirements during large target image change in scale, background outliers, and the necessity to perform (semi)autonomous relative navigation in the presence of limited resources (fuel, onboard computer hardware, etc). This paper proposes a relative navigation scheme in space that makes use of three different ingredients. First, two different feature detectors are used to ensure reliable feature detection over diverse distances, and subsequently fast feature selection/filtering is applied to detect the visual features of the fiducial marker. Next, a feature-pattern matching algorithm via robust affine registration is used for relative navigation to achieve robust automated re-acquisition in case of a lost target. Finally, a probabilistic graphical model-based fixed-lag smoothing based on factor graphs is used to accurately propagate relative translation and orientation 6-DOF state estimates and their velocities. The proposed approach is validated on hardware-in-the-loop 5-DOF spacecraft simulation facility at Georgia Tech.
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    A State-Dependent Riccati Equation Approach to Atmospheric Entry Guidance
    (Georgia Institute of Technology, 2010-08) Steinfeldt, Bradley A. ; Tsiotras, Panagiotis
    This paper investigates the use of state-dependent Riccati equation control for closed-loop guidance of the hypersonic phase of atmospheric entry. Included are a discussion of the development of the state-dependent Riccati equations, their outgrowth from Hamilton-Jacobi-Bellman theory, a discussion of the closed-loop nonlinear system's closed-loop stability and robustness from both a theoretical and practical viewpoint. An innovative use of sum-of-squares programming is used to solve the state-dependent Riccati equation with application of a state-dependent Riccati equation derived guidance algorithm to a high mass, robotic Mars entry example. Algorithm performance is compared to the Modified Apollo Final Phase algorithm planned for use on the Mars Science Laboratory.