Generic Drone Control Platform for Autonomous Capture of Cinema Scenes

The movie industry has been using Unmanned Aerial Vehicles as a new tool to produce more and more complex and aesthetic camera shots. However, the shooting process currently rely on manual control of the drones which makes it difficult and sometimes inconvenient to work with. In this paper we address the lack of autonomous system to operate generic rotary-wing drones for shooting purposes. We propose a global control architecture based on a high-level generic API used by many UAV. Our solution integrates a compound and coupled model of a generic rotary-wing drone and a Full State Feedback strategy. To address the specific task of capturing cinema scenes, we combine the control architecture with an automatic camera path planning approach that encompasses cinematographic techniques. The possibilities offered by our system are demonstrated through a series of experiments

Comparison of PID and Fuzzy Controller for Position Control of AR.Drone

This paper describes the implementation of the PID Controller to control the position of the AR.Drone in the x-y-z. This position control scheme uses three PID controllers to maintain the position of x, y and z using the signal control pitch, roll and vertical rate. PID Controller implemented on AR.Drone 2.0 and then tested in an indoor space. The performance of the controller will be compared with Fuzzy Logic Controller schemes that have been implemented previously. The results show that the PID Controller generate a response with rise time less than 3 seconds at the x and y position with around 25% overshoot. The result for z position give better result without overshoot. The comparison between fuzzy logic and PID Controller indicates that the results of the PID controller is better although there is overshoot

ESTIMASI PARAMETER MODEL HEIGHT-ROLL-PITCH-YAW AR DRONE DENGAN LEAST SQUARE METHOD

Pemodelan AR Drone di Jurusan Teknik Elektro Universitas Surabaya telah dimulai dengan menggunakan pendekatan sistem fisik AR Drone namun hasilnya belum memuaskan. Pada Tugas Akhir ini dirancang model AR Drone dengan menggunakan pendekatan data modeling. Struktur model AR Drone akan dicari parameter modelnya dengan menggunakan least square method. Proses pengambilan data dilakukan dengan menerbangkan AR Drone dengan menggunakan program yang dibuat pada pada ground station. Secara umum, prosedur pengambilan data untuk pemodelan dan validasi dilakukan dengan menerbangkan AR Drone hingga stabil pada ketinggian 1 meter kemudian diberikan step input tertentu sesuai dengan model yang akan dicari. Hasil dari pemodelan yang dilakukan di indoor sudah cukup memuaskan, sedangkan di outdoor tidak memuaskan. AR Drone’s modeling in the Department of Electrical Engineering at University of Surabaya has begun using the approach of physical systems from the drone but the result has not been satisfactory. In this final project, AR Drone’s modeling is designed by using data modeling approach. AR Drone’s structure model will be searched its model parameters by using least square method. The process to record the data is performed by flying the drone with a program which made with LabVIEW software. In general, the data collection procedures for modeling and validation is performed by flying the drone and let it stable at an altitude of 1 meter, and then gave step input according to the model that would be searched. The modeling result which performed at indoor is satisfactory, but at outdoor is not satisfactory

ESTIMASI PARAMETER MODEL HEIGHT-ROLL-PITCH-YAW AR DRONE DENGAN LEAST SQUARE METHOD

Pemodelan AR Drone di Jurusan Teknik Elektro Universitas Surabaya telah dimulai dengan menggunakan pendekatan sistem fisik AR Drone namun hasilnya belum memuaskan. Pada Tugas Akhir ini dirancang model AR Drone dengan menggunakan pendekatan data modeling. Struktur model AR Drone akan dicari parameter modelnya dengan menggunakan least square method. Proses pengambilan data dilakukan dengan menerbangkan AR Drone dengan menggunakan program yang dibuat pada pada ground station. Secara umum, prosedur pengambilan data untuk pemodelan dan validasi dilakukan dengan menerbangkan AR Drone hingga stabil pada ketinggian 1 meter kemudian diberikan step input tertentu sesuai dengan model yang akan dicari. Hasil dari pemodelan yang dilakukan di indoor sudah cukup memuaskan, sedangkan di outdoor tidak memuaskan. AR Drone’s modeling in the Department of Electrical Engineering at University of Surabaya has begun using the approach of physical systems from the drone but the result has not been satisfactory. In this final project, AR Drone’s modeling is designed by using data modeling approach. AR Drone’s structure model will be searched its model parameters by using least square method. The process to record the data is performed by flying the drone with a program which made with LabVIEW software. In general, the data collection procedures for modeling and validation is performed by flying the drone and let it stable at an altitude of 1 meter, and then gave step input according to the model that would be searched. The modeling result which performed at indoor is satisfactory, but at outdoor is not satisfactory

ESTIMASI PARAMETER MODEL HEIGHT-ROLL-PITCH-YAW AR DRONE DENGAN LEAST SQUARE METHOD

Pemodelan AR Drone di Jurusan Teknik Elektro Universitas Surabaya telah dimulai dengan menggunakan pendekatan sistem fisik AR Drone namun hasilnya belum memuaskan. Pada Tugas Akhir ini dirancang model AR Drone dengan menggunakan pendekatan data modeling. Struktur model AR Drone akan dicari parameter modelnya dengan menggunakan least square method. Proses pengambilan data dilakukan dengan menerbangkan AR Drone dengan menggunakan program yang dibuat pada pada ground station. Secara umum, prosedur pengambilan data untuk pemodelan dan validasi dilakukan dengan menerbangkan AR Drone hingga stabil pada ketinggian 1 meter kemudian diberikan step input tertentu sesuai dengan model yang akan dicari. Hasil dari pemodelan yang dilakukan di indoor sudah cukup memuaskan, sedangkan di outdoor tidak memuaskan. AR Drone’s modeling in the Department of Electrical Engineering at University of Surabaya has begun using the approach of physical systems from the drone but the result has not been satisfactory. In this final project, AR Drone’s modeling is designed by using data modeling approach. AR Drone’s structure model will be searched its model parameters by using least square method. The process to record the data is performed by flying the drone with a program which made with LabVIEW software. In general, the data collection procedures for modeling and validation is performed by flying the drone and let it stable at an altitude of 1 meter, and then gave step input according to the model that would be searched. The modeling result which performed at indoor is satisfactory, but at outdoor is not satisfactory

Comparison of PID and Fuzzy Controller for Position Control of AR.Drone

This  paper  describes  the  implementation  of  the  PID  Controller  to  control  the position of the AR.Drone in the x-y-z. This position control scheme uses three PID controllers to maintain the position of x, y and z using the signal control pitch, roll and vertical rate. PID Controller implemented on AR.Drone 2.0 and then tested in an indoor space. The performance of the  controller  will  be  compared  with  Fuzzy  Logic  Controller  schemes  that  have  been implemented previously. The results show that the PID Controller generate a response with rise time less than 3 seconds at the x and y position with around 25% overshoot. The result for z position give better result without overshoot.   The comparison between fuzzy logic and PID Controller indicates that the results of the PID controller is better although there is overshoot

X-COPTER STUDIO

We present a project that aggregates various existing robotic software and serves as a platform to conveniently control a quadrocopter, mainly for research or educational purposes. User interface runs in a browser and other components are also made with portability in mind. We provide a common interface that unifies different quadrocopter models and we implemented it for the Parrot AR.Drone 2.0. The platform is data oriented, i.e., it is based on dataflow between user objects. We implemented several such objects for: data recording and replaying, inertial and visual localization and following a given path

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions

Low-cost quadrotor hardware design with PID control system as flight controller

In designing an Unmanned Aerial Vehicle (UAV), such as quadrotor, sometimes an engineer should consider the required cost that is relatively expensive. As we know, quadrotor is one of robots that very usefull and has several advantages for human needs such as disaster area monitoring, air quality monitoring, area mapping, aerial photography, and surveillance. Thus, designing a rapid quadrotor with low-cost components and simple control system needs to be considered here. This paper presents design and implementation of a quadrotor using relatively low-cost components with Proportional Integral Derivative (PID) control system as its controller. The components used consist of microcontroller, Inertial Measurement Unit (IMU) sensor, Brushless Direct Current (BLDC) motor, Electronic Speed Control (ESC), remote control unit, battery, and frame. These components can be easily found in the electronic markets, especially in Indonesia. As an addition, this paper also describes PID control system as flight controller. A simple economic analysis is presented to clarify the cost in designing this quadrotor. Based on experimental testing result, the quadrotor able to fly stably with PID controller although there still overshoot at the attitude responses