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Tsiotras, Panagiotis

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Now showing 1 - 10 of 59
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    Research Adventures at the Intersection of Control and Robotics
    (Georgia Institute of Technology, 2022-08-24) Tsiotras, Panagiotis
    IRIM hosts each semester a symposium to feature presentations from faculty and presentations of research that has been funded by our IRIM seed grant program in the last year. The symposium is a chance for faculty to meet new PhD students on campus, as well as a chance to get a better idea of what IRIM colleagues are up to these days. The goal of the symposium is to spark new ideas, new collaborations, and even new friends!
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    Research Adventures at the Intersection of Control and Robotics
    (Georgia Institute of Technology, 2021-08-25) Tsiotras, Panagiotis
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    Performance Analysis of Three Cost Policies for the Control of a Camera in Relative Circumnavigation Scenarios
    (Georgia Institute of Technology, 2016-09) Antonello, Andrea ; Carron, Andrea ; Carli, Ruggero ; Tsiotras, Panagiotis
    In this paper, we address the relative navigation problem of a chaser circumnavigating a target. The chaser has an on-board camera and observes a set of features on the target; the goal is to obtain a detailed map of the landmarks. By controlling the yaw-rotation of the sensor it is possible to maximize the time allocated to landmark observation. An Extended Kalman Filter (EKF) provides state uncertainty information, which can then be used to design a cost function to be minimized by the optimal yaw controller. Three different cost functions are designed and simulated, and their performances are compared with the case of a xed, nadir-pointing camera. The analysis of localization uncertainties for different sets of initial conditions con rmed the superior performance of the proposed novel control methodology.
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    Vision-Based Attitude Determination Using A SLAM Algorithm During Relative Circumnavigation Of Non-cooperative Objects
    (Georgia Institute of Technology, 2016-09) Antonello, Andrea ; Tsiotras, Panagiotis
    We approach the problem of a chaser satellite circumnavigating a target object in a relative orbit. The objective is to obtain a map of the scenario and to measure the reciprocal position of the chaser-target pair, in order to subsequently perform proximity operations (active debris removal, rendezvous, servicing, etc.) more reliably. This work analyzes the case of a target-chaser scenario in a closed Clohessy-Wiltshire relative orbit. The chaser satellite has a vision sensor and observes a set of landmarks on the target satellite: the control acts on the yaw-rotation of the detector. By de ning a probability distribution over a set of feasible control trajectories, we perform a search for a near-optimal solution. At the core of this approach lies the cross entropy minimization technique for estimating rare-event probabilities, which iteratively approximates the sampling distribution towards regions of progressively lower cost until converging to the optimum. We present simulations of a tracking scenario, demonstrating the validity of the proposed control technique. Performance of the proposed policy is compared with the case of a non controlled sensor by evaluating the time spent under observation and the residual uncertainty bounds on the landmarks. Results con rm the validity of the proposed approach.
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    Adaptive Position and Attitude-Tracking Controller for Satellite Proximity Operations Using Dual Quaternions
    (Georgia Institute of Technology, 2015) Filipe, Nuno ; Tsiotras, Panagiotis
    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.
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    An Optimal Evader Strategy in a Two-Pursuer One-Evader Problem
    (Georgia Institute of Technology, 2014-12) Sun, Wei ; Tsiotras, Panagiotis
    We consider a relay pursuit-evasion problem with two pursuers and one evader. We reduce the problem to a one-pursuer/one-evader problem subject to a state constraint. A suboptimal control strategy for the evader to prolong capture is proposed and is compared to the optimal evading strategy. Extensions to the multiple-pursuer/one-evader case are also presented and evaluated via numerical simulations.
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    An Asymmetric Version of the Two Car Pursuit-Evasion Game
    (Georgia Institute of Technology, 2014-12) Exarchos, Ioannis ; Tsiotras, Panagiotis
    n this paper we consider a differential game of pursuit and evasion involving two players with constant, but different, speeds, and different maneuverability constraints. Specifically, the evader has limited maneuverability, while the pursuer is completely agile. This problem is an asymmetric version of the well-known Game of Two Cars. The aim of this paper is to derive the optimal strategies of the two players and characterize areas of initial conditions that lead to capture if the pursuer acts optimally, and areas that guarantee evasion regardless of the pursuer's strategy. It is shown that the problem reduces to a special version of Zermelo's Navigation Problem (ZNP) for the pursuer. Therefore, the well-known ZNP solution can be used to validate the results obtained through the differential game framework as well as to characterize the time-optimal trajectories. The results are directly applicable to collision avoidance problems.
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    Spectral Analysis of Extended Consensus Algorithms for Multiagent Systems
    (Georgia Institute of Technology, 2014-12) van de Hoef, Sebastian ; Dimarogonas, Dimos V. ; Tsiotras, Panagiotis
    We analyze an extension of the well-known linear consensus protocol for agents moving in two dimensions, where the standard consensus feedback is multiplied with a rotation matrix. This leads to a richer family of trajectories, and if only the new feedback term is applied, periodic solutions emerge. For special configurations of the controller gains, the form of the system trajectories is given in terms of the eigenvalues and eigenvectors of the closed-loop system matrix. We characterize the resulting closed-loop trajectories for specific choices of the controller gains and of the communication graph topology. Furthermore, the control strategy is extended to agents with double integrator dynamics. It is shown that stability is achieved with sufficiently large velocity feedback. The effect of this feedback on the overall system performance is further investigated. We finally provide simulations to illustrate the theoretical results.
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    Information-Theoretic Stochastic Optimal Control via Incremental Sampling-based Algorithms
    (Georgia Institute of Technology, 2014-12) Arslan, Oktay ; Theodorou, Evangelos A. ; Tsiotras, Panagiotis
    This paper considers optimal control of dynamical systems which are represented by nonlinear stochastic differential equations. It is well-known that the optimal control policy for this problem can be obtained as a function of a value function that satisfies a nonlinear partial differential equation, namely, the Hamilton-Jacobi-Bellman equation. This nonlinear PDE must be solved backwards in time, and this computation is intractable for large scale systems. Under certain assumptions, and after applying a logarithmic transformation, an alternative characterization of the optimal policy can be given in terms of a path integral. Path Integral (PI) based control methods have recently been shown to provide elegant solutions to a broad class of stochastic optimal control problems. One of the implementation challenges with this formalism is the computation of the expectation of a cost functional over the trajectories of the unforced dynamics. Computing such expectation over trajectories that are sampled uniformly may induce numerical instabilities due to the exponentiation of the cost. Therefore, sampling of low-cost trajectories is essential for the practical implementation of PI-based methods. In this paper, we use incremental sampling-based algorithms to sample useful trajectories from the unforced system dynamics, and make a novel connection between Rapidly-exploring Random Trees (RRTs) and information-theoretic stochastic optimal control. We show the results from the numerical implementation of the proposed approach to several examples.
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    Efficient Closed-Loop Detection and Pose Estimation for Vision-Only Relative Localization in Space with a Cooperative Target
    (Georgia Institute of Technology, 2014-08) Zhang, Guangcong ; Vela, Patricio A. ; Tsiotras, Panagiotis ; Cho, Dae-Min
    An integrated processing pipeline is presented for relative pose estimation of vision-only cooperative localization between two vehicles with unknown relative motion. The motivating scenario is that of proximity operations between two spacecraft when the target spacecraft has a special target pattern and the chase spacecraft is navigating using only a monocular visual sensor. The only prior information assumed is knowledge of the target pattern, which we propose to consist of nested circular blobs. The algorithm is useful for applications requiring localization accuracy using limited computational resources. It achieves low computational cost with high accuracy and robustness via the following contributions: (1) an adaptive visual pattern detection scheme based on the estimated relative pose, which improves both the e ciency of detection and accuracy of pose estimates; (2) a parametric blob detector called Box-LoG which is computationally e cient; and (3) an algorithm which jointly solves the frame-to-frame data association and relative pose estimation. An incremental smoothing technique temporally smooths the pose estimates. The approach can deal with target re-acquisition after loss of the target pattern from the field of view. The algorithm is tested in both synthetic simulations and on an actual spacecraft simulator platform.