Quadrotor Object Tracking using Real-Time Motion Sensing (PDF ...

Quadrotor Object Tracking using Real-Time Motion Sensing Ahmed Mashood, Ahmed Dirir, Mousa Hussein, Hassan Noura and Falah Awwad Department of Electrical Engineering, UAE University, Alain, Abu Dhabi, UAE e-mail: {a.mashood, 201350029, mihussein, hnoura, f_awwad}@uaeu.ac.ae Abstract—This paper presents a motion sensing platform based autonomous mobile object tracking using Unmanned aerial Vehicle (UAV). The position of the moving object was estimated using VICON motion capture camera system, and the information was processed using locally developed Matlab Simulink code. The UAV was assigned to navigate autonomously along the path of the moving vehicle and track it. The derived data was plotted and the efficiency of the tracking system is analyzed.

Keywords___ VICON Camera System, Parrot AR Drone 2.0, Matlab Simulink 1. INTRODUCTION UAVs are very much shaping up the future of aerospace industry and have substantially taken to the skies with military and civil applications, like monitoring and investigation of battlefields, border patrolling, monitoring public security, forest fire detection etc. UAVs have on-board cameras and processors, and are generally much lighter, smaller and cheaper compared to their piloted counterparts. Researchers are studying the aerodynamics of UAVs to develop control algorithms for autonomous navigation.

Using this setup, a coordinated formation flight between two UAVs were implemented to assess the accuracy of the position estimation algorithm [4][5]. It showed how unreliable UAVs onboard sensors are for high precision coordinated tasks. The paper is structured as follows: Section 1 is Literature Review. Section 2 will briefly explain the objects and devices used in the work. Section 3 will show the procedure and finally the results and conclusion will be discussed. 2.

METHODOLOGY

The proposed system consists of different parts and make up the various subsystems which have separate control systems and ways of communication. All the subsystems work in tandem and are compiled together forming a complete system. The subsystems are Vicon Motion sensing system, computer (Base station), jumping sumo (Robotic moving ground vehicle) and AR Drones (UAV). Figure 1 shows the basic hardware setup of the proposed system and Figure 1 shows the High level Architecture of the system. A brief introduction to each component is given below.

This paper deals with rotary wing that are VTOL (Vertical takeoff and landing). These vehicles can be used in takeoff area limited places. Mashood et al.presented a frame work to navigate a single UAV using body gestures, in a GPS denied environment[1]. [2] Set up a leader-follower system with 2 different UAV’s. A motion sensing game console was used to track the leader for online pose estimation. The UAV’s maintained a safety distance of 2 Meter throughout the flight. A group of researchers from Shanghai Jiao Tong University designed and implemented Auto-control UAV flight system that is based on video image processing and PID flight control. However the system was vulnerable to noise [3]. In this paper, we present a platform to track a moving ground vehicle accurately and autonomously navigate the UAV to hover above the tracked object. The proposed system will be implemented in a GPS denied indoor environment equipped with Real-Time Motion sensing camera setup that is placed permanently around the UAV and ground vehicle.

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Figure 1: The proposed system

are used in biomechanics studies and animations. The Vicon system in use is shown in Figure 4 and is composed of 12 infrared cameras that are placed around object, and is used for motion tracking of reflective tapes called ‘markers’ placed on visual reference point on Objects. ‘Vicon Tracker’ is a tracking tool program developed by Vicon. The program triangulates the 3D position of the subject by processing the captured cues from the camera. More information about the Vicon system can be found at Vicon website [7]. Figure 1 shows UAV and Ground Vehicle equipped with reflective markers placed on top of it.

Figure 2: Proposed System Architecture Figure 3 : AR Drone and Jumping sumo The ‘ground vehicle navigation platform’ block in figure 2 is responsible for navigating the ground vehicle. The 3D positions of ground vehicle and UAV are then fetched using Vicon system and triangulated by the two respective ‘Ground vehicle position from Vicon camera’ and ‘UAV position from Vicon camera’ blocks. The ‘guidance logic’ block compares the two position information’s of UAV and ground vehicle. The ‘baseline controller’ block generates the new error signal to be send to the UAV. The ‘communication with AR Drone for navigation’ block sends the feedback to the UAV depending upon the error signal generated. A. AR Drone UAV AR Drone is an electrically powered flying quadcopter built by the French company ‘Parrot’. It is a radio controlled device which can be controlled by using mobile platforms such as Apple iPhone, Android devices and computers [6]. The First quadrotor from ‘Parrot’ was AR Drone version 1.0 revealed at the International CES 2010 in Las Vegas. AR Drone 2.0 was revealed in 2012. It's smaller in size and extremely steady and thus can be used as a part of reconnaissance mapping and policing. Joystick or RC-Transmitters can be utilized for remote steered route by the administrator. AR Drone has 6 degrees of freedom (DOF) built in inertial measurement unit. It can provide pitch, roll and yaw readings which can be used for automatic pitch, roll and yaw stabilization as well as assisted tilting control. B. Motion Capture System (Vicon System) Vicon system is a commercial 3D motion capture (MoCap) system. It has a latency of 1.9 milliseconds (ms). They

Figure 4 : UAEU Vicon Cameras C. Matlab Simulink Matlab is a high-level programming language platform that can perform computational task, and is a convenient interface for implementing real-time control operations. Matlab will be used here to develop algorithms to autonomously navigate the UAVs. Figure 6 illustrates the Matlab Simulink code developed for ground vehicle tracking and UAV navigation. Figure 6 shows how new reference pitch angle for UAV is derived from forward velocity of UAV and Ground vehicle

Figure 5: PID controller for Pitch angle

Parrot SA. The UAV is supposed to follow the Vehicle and form a square path.

Figure 7: Square Path Assigned to the Vehicle

4. RESULTS & DISCUSSION

Figure 6: Matlab Object Tracking Code D. Jumping Sumo (Programmable mobile robot) The jumping sumo is a two-wheeled vehicle, taking its concept and movement pattern from the hover board. The jumping sumo wheels are big to achieve balance. It has a spring loaded tail for balancing and jumping in two ways, vertically and trajectory. One of the useful features it has is the wide range camera placed in its nose for live stream in the tablet or mobile phone controlling the jumping sumo, and similar to the AR drone the jumping sumo has its own Wi-Fi network.

The Data from the system were saved and plotted. Figure 8 shows the 3D positions of UAV and Ground Vehicle. The UAV followed the path of the vehicle with a good accuracy. From Figure 9 which shows the 2D position, it can be observed the UAV deviated from the path when abrupt changes in path occurred. Figure 10 is the position comparison graph and it can be noticed that there was a constant delay in tracking. Table 1 shows the average time delay in tracking and is found to be 1.3 seconds. .

3. FRAME WORK IMPLEMENTATION The Vicon motion capture system senses the moving ground vehicle, and the instantaneous 3D position of the vehicle is obtained. This position is now considered as a reference position for the UAV, the Matlab Simulink process the real time information from the Vicon system, and directs the UAV to follow the new instantaneous position of the ground Vehicle. In order to evaluate the performance of the proposed system, an experiment is conducted inside a room of 5m X 7m X 4m Dimension. GPS tracking is not possible due to indoor environment. UAVs and the ground vehicles instantenous positions were tracked using the Vicon motion tracking system and plotted using matlab simulink code. Video recordings can be seen at[8] To test and verify the accuracy of the tracking algorithm, the jumping sumo is directed to move in a square path of 1.5m side length. The path shown in Figure 7 is implemented using the Free Flight Jumping mobile application developed by

Figure 8: 3D Positions

5. CONCLUSION The paper introduced a framework to Track a moving ground vehicle using an optical motion sensing camera setup and navigate an UAV to the path of vehicle. The motion tracking showed a great robustness. The UAV is capable of accurately flying autonomously and track the moving ground vehicle. The Simulink algorithm developed in UAEU UAV Lab is very efficient and effectively yielded a good result. However a major drawback of the system is its cost. The sensing cameras are very expensive.

Figure 9: 2D Positions

The time delay in tracking can be reduced by using better robust controllers. As part of future work a cooperative formation flight of multiple UAVs tracking a moving object is proposed. 6. REFERENCES [1]

[2]

[3] Figure 10: Position Comparison Table 1: Time Delay Values

[4]

[5]

[6]

[7] [8]

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