Copot, Cosmin

De Keyser, Robain

Mac Thi, Thoa

Tran Duc, Trung

English

Ghent University Academic Bibliography

Towards a navigation system for an autonomous UAV in indoorenvironmentThoa Mac Thi1,2, Cosmin Copot1, Trung Tran Duc2, and Robin De Keyser11Department of Dynamics Systems and Control (DySC), Ghent University, Belgium.2School of Mechanical Engineering, Hanoi University of Science and Technology, Vietnam.Thoa.MacThi@UGent.be1 IntroductionIn recent years, research interest in unmanned aerial vehi-cles (UAVs) has emerged due to their potential use for a widerange of applications such as: smart flying sensor, formationcontrol of unmanned ground vehicles (UGVs) using an UAVand habitat mapping. In order to accomplish the above men-tioned missions, a prerequisite requirement is that the UAVshould be able to implement real-time autonomous naviga-tion. Whereas most of the proposed approaches are suitablefor outdoors, only few techniques have been developed forindoor environments. In this paper, a solution using only on-board visual and inertial sensing which enables an UAV tooperate indoors is proposed. The approach comprises threekey components: pattern-based localization, IMU data pro-cess, designed path planning and controller. This method-ology opens new possibilities for the UAV to perform au-tonomous navigation.2 System setupThe proposed approach consists of three major componentsrunning on a laptop connected to the UAV (Ar. Drone 2.0)via wireless communication as shown in Figure 1. The firstcomponent is the pattern based localization which allowsAr. Drone 2.0 to determine its location and orientation in aworking space. The second component is IMU data processwhich transmits and receives signals between Ar. Drone 2.0and the ground station. The last component is a cascade con-trol which guides the drone to follow the desired trajectories.3 Path planning and control designThe paths are obtained base on modified A*, D* and Poten-tial Fields algorithms. To perform experiments, a cascadecontrol is designed (Figure 2) such that the drone followsthe generated trajectories. There are two parts of the cascadecontroller: inner-loop controller and outer-loop controller.The inner-loop controller is performed inside the drone asa black-box. The outer-loop controller is designed to im-plement position control. The localization process providesthe current the drone pose in world coordinate based on theground patterns. The obtained free-collision path is sent tothe controller by a list of way-points [1].Figure 1: The proposed navigation approach of an AR.Drone 2.0Figure 2: The proposed cascade controller of an AR.Drone 2.04 ConclusionIn this study, we have presented an indoor flight approachfor a low-cost commercial AR. Drone 2.0 using only on-board visual and internal sensing. The real-time experimentdemonstrates the feasibility of the proposed strategy whichopens an autonomous navigation possibility for the drone inindoor environment.References[1] Mac. T.T, Copot. C, Hernandez. A, De Keyser R,Improved Potential Field Method for Unknown ObstacleAvoidance Using UAV in Indoor Environment, IEEE 14thInternational Symposium on Applied Machine Intelligenceand Informatics, Herlany, Slovakia, pp. 345- 350, 2016.

Towards a navigation system for an autonomous UAV in indoor environment

https://biblio.ugent.be/publication/7204232/file/7204238.pdf

Towards a navigation system for an autonomous UAV in indoor environment

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