Person:

Tsiotras, Panagiotis

Permanent Link

https://hdl.handle.net/1853/71790

Associated Organization(s)

Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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Publication Search Results

Now showing 1 - 10 of 12

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.
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.
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.
Minimum-Time Paths for a Light Aircraft in the Presence of Regionally-Varying Strong Winds

(Georgia Institute of Technology, 2010) Bakolas, Efstathios ; Tsiotras, Panagiotis

We consider the minimum-time path-planning problem for a small aircraft flying horizontally in the presence of obstacles and regionally-varying strong winds. The aircraft speed is not necessarily larger than the wind speed, a fact that has major implications in terms of the existence of feasible paths. First, it is possible that there exist configurations in close proximity to an obstacle from which a collision may be inevitable. Second, it is likely that points inside the obstacle-free space may not be connectable by means of an admissible bidirectional path. The assumption of a regionally-varying wind field has also implications on the optimality properties of the minimum-time paths between reachable configurations. In particular, the minimum-time-to-go and minimum-time-to-come between two points are not necessarily equal. To solve this problem, we consider a convex subdivision of the plane into polygonal regions that are either free of obstacles or they are occupied with obstacles, and such that the vehicle motion within each obstacle-free region is governed by a separate set of equations. The equations of motion inside each obstacle-free region are significantly simpler when compared with the original system dynamics. This approximation simplifies both the reachability/accesibility analysis, as well as the characterization of the locally minimum-time paths. Furthermore, it is shown that the minimum-time paths consist of concatenations of locally optimal paths with the concatenations occurring along the common boundary of neighboring regions, similarly to Snell’s law of refraction in optics. Armed with this representation, the problem is subsequently reduced to a directed graph search problem, which can be solved by employing standard algorithms.
Bank-to-Turn Control for a Small UAV using Backstepping and Parameter Adaptation

(Georgia Institute of Technology, 2008-07) Jung, Dongwon ; Tsiotras, Panagiotis

In this research we consider the problem of path following control for a small fixed-wing unmanned aerial vehicle (UAV). Assuming the UAV is equipped with an autopilot for low level control, we adopt a kinematic error model with respect to the moving Serret-Frenet frame attached to a path for tracking controller design. A kinematic path following control law that commands heading rate is presented. Backstepping is applied to derive the roll angle command by taking into account the approximate closed-loop roll dynamics. A parameter adaptation technique is employed to account for the inaccurate time constant of the closed-loop roll dynamics during actual implementation. The path following control algorithm is validated in real-time through a high-fidelity hardware-in-the-loop simulation (HILS) environment showing the applicability of the algorithm on a real system.
Multiresolution Path Planning Via Sector Decompositions Compatible to On-Board Sensor Data

(Georgia Institute of Technology, 2008) Bakolas, Efstathios ; Tsiotras, Panagiotis

In this paper we present a hybrid local-global path planning scheme for the problem of operating a moving agent inside an unknown environment in a collision-free manner. The path planning algorithm is based on information gathered on-line by the available on-board sensor devices. The solution minimizes the total length of the path with respect to a metric that includes actual path length along with a risk-induced metric. We use a multi-resolution cell decomposition of the environment in order to solve the path-planning problem using the wavelet transform in conjunction with a conformal mapping to polar coordinates. By performing the cell decomposition in polar coordinates we can naturally incorporate sector-like cells that are adapted to the data representation collected by the on-board sensor devices. Simulations are presented to test the efficiency of the algorithm using a non trivial scenario.
On-line Path Generation for Small Unmanned Aerial Vehicles using B-Spline Path Templates

(Georgia Institute of Technology, 2008) Jung, Dongwon ; Tsiotras, Panagiotis

In this study we investigate the problem of generating a smooth, planar reference path, given a family of discrete optimal paths. In conjunction with a path representation by a finite sequence of square cells, the generated path is supposed to stay inside a feasible channel, while minimizing certain performance criteria. Constrained optimization problems are formulated subject to geometric (linear) constraints, as well as boundary conditions in order to generate a library of B-spline path templates. As an application to the vehicle motion planning, the path templates are incorporated to represent local segments of the entire path as geometrically smooth curves, which are then joined with one another to generate a reference path to be followed by a closed-loop tracking controller. The on-line path generation algorithm incorporates the path templates such that continuity and smoothness are preserved when switching from one template to another along the path. Combined with the D∗-lite path planning algorithm, the proposed algorithm provides a complete solution to the obstacle-free path generation problem in a computationally efficient manner, suitable for real-time implementation.
Beyond Quadtrees: Cell Decomposition for Path Planning using the Wavelet Transform

(Georgia Institute of Technology, 2007-12) Cowlagi, Raghvendra V. ; Tsiotras, Panagiotis

Path planning techniques based on hierarchical multiresolution cell decompositions are suitable for online implementation due to their simplicity and speed of implementation. We present an efficient multiresolution cell decomposition scheme based on the Haar wavelet transform. The decomposition approximates the environment using high resolution close to the agent and coarse resolution elsewhere. We demonstrate an algorithm to extract the adjacency and transition cost relations of the cells directly from the wavelet transform coefficients.
A Hierarchical On-Line Path-Planning Scheme Using Wavelets

(Georgia Institute of Technology, 2007-07) Tsiotras, Panagiotis ; Bakolas, Efstathios

We present an algorithm for solving the shortest (collision-free) path planning problem for an agent (e.g., wheeled vehicle, UAV) operating in a partially known environment. The agent has detailed knowledge of the environment and the obstacles only in the vicinity of its current position. Far away obstacles or the final destination are only partially known and may even change dynamically at each instant of time. We obtain an approximation of the environment at different levels of fidelity using a wavelet approximation scheme. This allows the construction of a directed weighted graph of the obstacle-free space in a computationally efficient manner. In addition, the dimension of the graph can be adapted to the on-board computational resources. By searching this graph we find the desired shortest path to the final destination using Dijkstra's algorithm, provided that such a path exists. Simulations are presented to test the efficiency of the algorithm using non trivial scenarios.
Modelling and Hardware-in-the-Loop Simulation for a Small Unmanned Aerial Vehicle

(Georgia Institute of Technology, 2007-05) Jung, Dongwon ; Tsiotras, Panagiotis

Modeling and experimental identification results for a small unmanned aerial vehicle (UAV) are presented. The numerical values of the aerodynamic derivatives are computed via the Digital DATCOM software using the geometric parameters of the airplane. Flight test data are utilized to identify the stability and control derivatives of the UAV. The aerodynamic angles are estimated and used in conjunction with inertial measurements in a batch parameter identification algorithm. A hardware-in-the-loop (HIL) simulation environment is developed to support and validate the UAV autopilot hardware and software development. The HIL simulation incorporates a high-fidelity dynamic model that includes the sensor and actuator models, from the identified parameters from experiments. A user-friendly graphical interface that incorporates external stick commands and 3-D visualization of the vehicle’s motion completes the simulation environment. The hardware-in-the-loop setup is an indispensable tool for rapid certification of both the avionics hardware and the control software, while performing simulated flight tests with minimal cost and effort.