Organizational Unit:

Unmanned Aerial Vehicle Research Facility

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https://hdl.handle.net/1853/70748

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Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1139

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Publication Search Results

Now showing 1 - 10 of 105

The Semi-Coaxial Multirotor

( 2018-05) Bershadsky, Dmitry ; Haviland, Stephen ; Johnson, Eric N.

The ”semi-coaxial” multirotor configuration is presented including its advantages over the conventional coaxial rotor configuration. The semi-coaxial configuration retains the benefits of the coaxial configuration, and additionally alleviates the loss of efficiency encountered when rotors are stacked coaxially. In addition to being more power-efficient than the standard coaxial configuration, the described configuration allows for nearly- or fully-actuated control of a multirotor when used in configurations such as the three-armed Y6 hexarotor. Using this configuration, a new Direct Force Control (DFC) multirotor is presented: the Y6sC, a specific example of the semi-coaxial multirotor. The configuration orients six rotors in a way which allows the vehicle to hover in non-zero attitudes and translate without rotating with higher efficiency than the corresponding coaxial design.
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.
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.
Vision-Based Optimal Landing On a Moving Platform

(Georgia Institute of Technology, 2016-05) Nakamura, Takuma ; Haviland, Stephen ; Bershadsky, Dmitry ; Johnson, Eric N.

This paper describes a vision-based control architecture designed to enable autonomous landing on a moving platform. The landing trajectory is generated by using the receding-horizon differential dynamic programming (DDP), an optimal control method. The trajectory generation is aided by the output of a vision-based target tracking system. The vision system uses multiple extended Kalman filters which allows us to estimate the position and heading of the moving target via the observed locations. The combination of vision-based target tracking system and the receding-horizon DDP gives an unmanned aerial vehicle the capability to adaptively generate a landing trajectory against tracking errors and disturbances. Additionally, by adding the exterior penalty function to the cost of the DDP we can easily constrain the trajectory from collisions and physically infeasible solutions. We provide key mathematics needed for the implementation and share the results of the image-in-the-loop simulation and flight tests to validate the suggested methodology.
Vision-Based Closed-Loop Tracking Using Micro Air Vehicles

(Georgia Institute of Technology, 2016) Nakamura, Takuma ; Haviland, Stephen ; Bershadsky, Dmitry ; NodeIn, Daniel Magree ; Johnson, Eric N.

This paper describes the target detection and tracking architecture used by the Georgia Tech Aerial Robotics team for the American Helicopter Society (AHS) Micro Aerial Vehicle (MAV) challenge. The vision system described enables vision-aided navigation with additional abilities such as target detection and tracking all performed onboard the vehicles computer. The author suggests a robust target tracking method that does not solely depend on the image obtained from a camera, but also utilizes the other sensor outputs and runs a target location estimator. The machine learning based target identification method uses Haar-like classifiers to extract the target candidate points. The raw measurements are plugged into multiple Extended Kalman Filters (EKFs). The statistical test (Z-test) is used to bound the measurement, and solve the corresponding problem. Using Multiple EKFs allows us not only to optimally estimate the target location, but also to use the information as one of the criteria to evaluate the tracking performance. The MAV utilizes performance-based criteria that determine whether or not to initiate a maneuver such as hover or land over/on the target. The performance criteria are closed in the loop which allows the system to determine at any time whether or not to continue with the maneuver. For Vision-aided Inertial Navigation System (VINS), a corner Harris algorithm finds the feature points, and we track them using the statistical knowledge. The feature point locations are integrated in Bierman Thornton extended Kalman Filter (BTEKF) with Inertial Measurement Unit (IMU) and sonar sensor outputs to generate vehicle states: position, velocity, attitude, accelerometer and gyroscope biases. A 6- degrees-of-freedom quadrotor flight simulator is developed to test the suggested method. This paper provides the simulation results of the vision-based maneuvers: hovering over the target, and landing on the target. In addition to the simulation results, flight tests have been conducted to show and validate the system performance. The 500 gram Georgia Tech Quadrotor (GTQ)- Mini, was used for the flight tests. All processing is done onboard the vehicle and it is able to operate without human interaction. Both of the simulation and flight test results show the effectiveness of the suggested method. This system and vehicle were used for the AHS 2015 MAV Student Challenge where the GPS-denied closed-loop target search is required. The vehicle successfully found the ground target, and landed on the desired location. This paper shares the data obtained from the competition.
Efficient Approximation of Optimal High-Order Kinematic Trajectories

(Georgia Institute of Technology, 2016-01) Mooney, John ; Johnson, Eric N.

A method for efficiently planning one-dimensional pop-limited trajectories is presented, along with a direct method for synchronizing trajectories across multiple dimensions. This heuristic is designed for a double integrator utilizing acceleration commands passed through a 4th-order cascaded filter, the model for which is presented along with the system solution for an arbitrary time step and derivative limits. Examples for trajectories generated in both one and two dimensions are shown, with comparison to an iterative solver which searches for the exact optimal solution. The presented algorithm shows drastically lower computational requirements than the iterative solver, with very little cost in accuracy. Benefits and limitations of this approach are discussed.
Development of a 500 gram Vision-based Autonomous Quadrotor Vehicle Capable of Indoor Navigation

(Georgia Institute of Technology, 2015-05) Haviland, Stephen ; Bershadsky, Dmitry ; Magree, Daniel ; Johnson, Eric N.

This paper presents the work and related research done in preparation for the American Helicopter Society (AHS) Micro Aerial Vehicle (MAV) Student Challenge. The described MAV operates without human interaction in search of a ground target in an open indoor environment. The Georgia Tech Quadrotor-Mini (GTQ-Mini) weighs under 500 grams and was specifically sized to carry a high processing computer. The system platform also consists of a monocular camera, sonar, and an inertial measurement unit (IMU). All processing is done onboard the vehicle using a lightweight powerful computer. A vision navigation system generates vehicle state data and image feature estimates in a vision SLAM formation using a Bierman Thornton extended Kalman Filter (BTEKF). Simulation and flight tests have been performed to show and validate the systems performance.
A Monocular Vision-aided Inertial Navigation System with Improved Numerical Stability

(Georgia Institute of Technology, 2015-01) Magree, Daniel ; Johnson, Eric N.

This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop.
Longitudinal Motion Planning for Slung-Loads Using Simplified Models and Rapidly-Exploring Random Trees

(Georgia Institute of Technology, 2015-01) Johnson, Eric N. ; Mooney, John G.

A randomized motion-planning approach to providing guidance for helicopters with under-slung loads is presented. Rapidly-exploring Random Trees are adapted to plan trajectories for simplified helicopter-load models. Four different planning models are tested against four different representative tasks. The poor performance of the baseline planner, and subsequent efforts to improve that performance shows the sensitivity of the RRT to proper sizing of the sampling area and amount of computation available. Further lines of potential research into optimizing planner performance and reducing computational cost are identified.
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.