Design, Trajectory Generation and Control of Quadrotor ResearchPlatform

Durgesh Haribhau Salunkhe1, Siddhant Sharma1, Sujal Amrit Topno1, Chandana Darapaneni2

Amol Kankane3 and Suril V Shah 4

Abstract— We describe the modeling, estimation and controlof a quadrotor in 3D environment using the 3DR PixhawkPX4 as controller through Robot Operating System(ROS). Thepaper discusses a method to measure moment of inertia ofquadrotor about its principal axes to achieve better results inan inexpensive way. We also present the trajectory generationand segment optimization of the trajectory commanded to thequadrotor. We describe a method of controlling the quadrotorthrough ROS by providing necessary inputs to the flightcontroller using the built-in firmware.

I. INTRODUCTION

In the recent decade there has been a rise of interest inquadrotors and its control. Quadrotors consist of four pro-pellers having fixed-pitch blades, attached to motors mountedon a rigid cross frame configuration. Vertical Take-Off andLanding (VTOL) and hovering like a conventional helicopteris one of the major benefits of such multirotor platforms [1].Few applications of quadrotors include search and rescue [2],surveillance [3], reconnaissance and data acquisition. Variousperipheral devices can be mounted on the quadrotor as perthe required application. Quadrotors are simple to model asno swash-plate mechanism is required. Being under-actuated,the dynamic model of a quadrotor consists of non-linearand multivariate equations. To have a better control overquadrotors, it is very important to have accurate valuesof physical parameters. The inertia along principal axes iseither calculated theoretically [4] or by modeling in CADsoftwares. The inertia values calculated by this method maydeviate from the actual performance due to assumptions andmistakes in CAD modeling.

Trajectory generation of the quadrotor is based on optimiz-ing the input parameters. [5] and [6] have proposed a cubicpolynomial trajectory or a minimum acceleration trajectory.[7] discusses about minimum jerk trajectory and its perfor-mance with quadrotors. Though these trajectories create asmooth path, the optimizing parameter of the quadrotor is

This work was supported by Suril Shah, Asst. Prof, IIT Jodhpur, Ra-jasthan.

1Durgesh Haribhau Salunkhe, Siddhant Sharma and Sujal Amrit Topnoare Undergraduate Students at Birla Institute of Technology, Mesra, Ranchisalunkhedurgesh@gmail.com

2Chandana Darapaneni is an Undergraduate Student at Indian Institute ofTechnology, Jodhpur, Rajasthan

3Amol Kankane is an Undergraduate Student at Indian Institute ofTechnology(BHU) Varanasi

4Suril V Shah is a Faculty member, Mechanical engineering, IndianInstitute of Technology,Jodhpur.

Fig. 1: Quadrotor build and frames in ’X’-configuration

snap, the fourth derivative of position. The minimum snaptrajectory generates smooth transition through given set ofwaypoints [8]. Trajectory is controlled by feeding necessaryinputs which are a function of time. Robust flight controllersare available which allow us to follow the generated trajec-tories with accuracy.

3DR Pixhawk v2 PX4 is one of such flight controllers.Pixhawk provides real time flight data transmission, suitablefor both research as well as on-field applications. The opensource firmware provided by Pixhawk is continuously up-graded by a large community of developers. Research basedon open source platforms prevents one from wasting effort onwork already achieved. Control of an open source platform,Mikrokopter, has been reported earlier [1]. Implementationof common robotic algorithms is simplified using ROS. Thedata streaming and communication with Flight Control Unit(FCU) is done using the MAVLink protocol.Various methods for outdoor as well as indoor state esti-

mation have been explored so far. The work reported wasperformed in a laboratory setup and so the quadrotor wasmaneuvered in a constrained and well defined space. Weuse VICON motion capture system to estimate the state ofthe quadrotor. VICON is a vision-based global localizationsystem. It serves the purpose of estimating all states requiredto control a quadrotor. This system is reliable and providesan accurate estimation of the quadrotor.

We propose a method that enables us to get accuratevalues of moment of inertia in a safe and inexpensive

manner. A method of tuning gain values for roll and pitchof the quadrotor is also mentioned. The relation of thrustand reaction moment with the rpm of motors is calculatedby using momentum theory [9]. An experimental setup isproposed to measure the proportionality constants. We gen-erate minimum snap trajectory and also propose a method tooptimize segment time allocation for the trajectory. Controlof the quadrotor from Robot Operating System (ROS) usingthe MAVROS package on an off board computer is alsodiscussed in the paper.

Section II discusses the design considerations of thequadrotor. The measurement of the parameters related todynamic modeling of the quadrotor are also detailed in thissection. In Section III the dynamic modeling and linearcontrol of the quadrotor has been described along withtrajectory generation and segment optimization. In SectionIV, the paper details the flight controller used and the stateestimation of a quadrotor using VICON, it also explains thecommunication by use of ROS. We present our results inSection V and put forward future work in Section VI.

II. DESIGN CONSIDERATIONS

A quadrotor has to be chosen with all considerationsrelated to the application for which it is used. We explainthe design process of selecting components and contributionof each component in the performance of the quadrotor.

A. Design of the Quadrotor

We built a quadrotor which followed a particular giventrajectory while carrying a considerable payload such as amanipulator [13] or any other sensor like laser scanner [14]which are extensively used in research on quadrotor. Theprocess of selecting the components is described in Fig. 2.The deciding parameters were payload and the enduranceof the quadrotor. The weight of the quadrotor built is 1.12kg and has flight time of 7 minutes with a 3S 4000 mAhLithium Polymer (LiPo) battery. The quadrotor can carry apayload of maximum 900 grams. The size of the frame is450mm measured diagonally. Z-blade propellers of 9.4 inchdiameter with a pitch of 5 inch are used to achieve a thrust toweight ratio of 2.1. The quadrotor was optimized in terms ofits maneuvering capabilities and payload capacity. We chosePixhawk V2 PX4 as our flight controller due to its advantagesdiscussed in Section IV. Preliminary calculations were doneto calculate thrust to weight ratio, flight time and angularacceleration of the quadrotor.

B. Measurement of Thrust and Reaction Moment

We calculated the maximum thrust and reaction momentprovided by the motors. The thrust was estimated theoret-ically, using momentum theory. The relation of thrust andthe reaction moment is proportional to ω2. We estimatedthe coefficients that related thrust and reaction moment withthe square of the angular velocity of the motors. Theseexperiments were performed in order to have a better controlover the dynamics of the quadrotor.

Size ofthe frame

Size of thepropeller

Motorsand ESC

Battery

Flightcontroller

OtherAccessories

If changes are to be made

Decides agility Decides payload

Decides flight time

Depends onApplication

Depends onflying environment

Fig. 2: Design process for component selection

The proportionality constants Kt and Km are the prime pa-rameters to be measured. The actual net thrust and momentsprovided by the rotors were calculated by the experimentalsetup in Fig. 3 and 4. For the experiment, an L-shaped rigidstructure made of wood was pivoted at the intersection of thearms. A weighing pan was placed under one arm to measurethe thrust. The motor was mounted in such a manner that thethrust generated reflected as weight on the weighing pan asshown in Fig. 3. A laser tachometer was used to estimate therpm of the motor. The thrust measured was tabulated againstω2.The formula used :

Kt =Wl1

l2 ω2 + c1 (1)

Where W is the force exerted on the weighing scale measuredin Newtons. c1 is the constant that showed the offset of theactual result from the one expected. The average was takenand value of Kt was calculated as 1.10× 10−7 and c1 wasapproximately 1.10×10−3

For the computation of Km, the motor was mounted onthe adjacent face of the wooden block as shown in Fig.4. The moment was calculated by measuring the force onthe weighing pan. The reaction moment was plotted againstthe square of angular velocity. Km was calculated using thefollowing relation:

Km =Wl1ω2 + c2 (2)

Where l1 = l2 = 18cm, is length of the arms of the structureused. The average Km came out to be = 2.94×10−9 withoutany offset (c2 = 0).

Fig. 3: Setup for measuringthrust

Fig. 4: Setup for measuringreaction moment

Fig. 5: Top view of test rig showing 3 DOFs

C. Measurement of Inertia Tensor

In order to measure the next set of parameters as perrequired applications, a test rig was designed, shown in Fig.5. We measured the moment of inertia along the principalaxes and tuned the gain values for roll and pitch angles usingthe mentioned test rig. A test bench that measures all 6 DOFsof the quadrotor has been built by [15]. Though the testbench is capable of measuring all DOFs, the cost of suchtest benches is high. While using a ball joint mechanism,the roll and pitch axes don’t necessarily pass through thecenter of gravity of the quadrotor which may create an errorin the result. The proposed test rig is capable of measuringall the rotational DOFs in an inexpensive manner. It consistsof three frames forming a gimbal, a mechanism that hasthree rotational degrees of freedom. The experiments wereperformed with the quadrotor mounted on the test rig aboutthe pitch axis. The shaft that extended from quadrotor passedthrough the center of gravity of the quadrotor which helpedin reducing the errors in tuning of the quadrotor. Opticalshaft encoders with a resolution of 0.02 degrees were usedto measure the rotations about the 3 axes.

Moment of inertia of the quadrotor is an important param-eter that directly governs the control of quadrotor. Most ofthe literature currently available focuses on measuring Ixx, Iyy

Fig. 6: Plot of angular speed vs time for measuring Ixx

and Izz theoretically [4] or by the use of CAD softwares.Use of CAD requires a detailed design of the Quadrotorin the software for accurate figures to be achieved. In ourapproach we used the test rig to measure the values of Ixxand Iyy experimentally. We mounted the quadrotor in thetest rig as described and rotated motor 1 and 3 shown inFig. 1 which would provide pitching of the quadrotor. Thequadrotor was held stationary with the motors 1 and 3 (Fig.1)rotating till a constant rpm of motors was measured and thenthe quadrotor was set free to rotate. We obtained the plot ofangular velocity of the rotating quadrotor against time. Thequadrotor accelerated initially to attain a constant angularvelocity as shown in Fig. 6. This accounts to the drag forcesacting on the quadrotor. These forces also contribute in theangular acceleration for pitching. As these forces are notcalculated, the theoretical relation of Moment and the angularacceleration do not hold true. In the experiment performed,we estimated near to actual relation of moment and angularacceleration of the quadrotor. The moment was calculatedfrom the thrust corresponding to the rpm of the motors fromprevious experiment. Angular acceleration (α) was obtainedas the slope of ω v/s time graph till the red line shown inFig. 6. The inertias were then calculated by using the relationbetween the moments and angular acceleration achieved.

M = Ktω2× L√

2×2 (3)

α =ω

t(4)

Ixx,yy =Mx,y

αx,y(5)

Fig. 7: Quadrotor suspended for measuring Izz

In general Izz is approximated to be the sum of Ixx andIyy. We used the concept of bifilar pendulum to measure Izz.Two vertical strings were used to suspend the quadrotor inhorizontal position as shown in Fig. 7. On giving a smallangular displacement about the yaw axis. The quadrotorexhibits oscillations. The moment of inertia can be measuredusing the equation:

Izz =mg T 2d2

4π2l(6)

Where, T is the time period oscillations, 2d is the distancebetween two string, and l is the length of the strings. Here,we measured T = 1.65sec, l = 0.38m and d = 0.105m.

Izz = 0.022kgm2

The test rig was also used to tune gain values for thepitch and roll control. Pixhawk Ground Control Station(GCS)provided the flexibility of tuning the Kp, Kd and Ki valuesof roll, pitch and yaw movements. Pitch angle was given tothe quadrotor mounted on the test rig using the transmitterradio and data from the encoders was used to decide over thegain values. We adopted Ziegler - Nichols rule for tuning thegain values. Kd and Ki were reduced to zero. The Kp wasincreased from zero, until a point where stable oscillationswere observed. Ki was decided according to the heuristicmethod till the maximum value of Kp to avoid the steadystate error in the quadrotor. Kd , which governs the dampingin error correction was tuned by the same method till anoptimum value was achieved. Same process was adopted fortuning the gains for roll. The quadrotor was mounted in sucha manner that the roll axis coincided with the previous pitchaxis. This was done in order to avoid the effect of the inertiaof the frame of the test rig.

III. MODELLING AND CONTROL

There were two possible configurations of the quadrotor tobe chosen from viz. ’+’ configuration and ’X’ configuration.In a ’+’ configuration, the roll and pitch axes are along thearms of the quadrotor whereas in an ’X’ - configuration theroll and pitch axes are shifted 45 degrees from the armsof the quadrotor. We preferred ’X’ configuration over ’+’configuration as the ’X’ configuration had advantages indynamics over the other configuration. In ’X’ configurationall the 4 motors are responsible for roll and pitch control.This gives a thrust advantage over the other configurationby a factor of

√2. Also, the configuration allows better use

of sensors or cameras as the propellers don’t interfere in theline of sight. As the quadrotor is expected to carry a payload,it is always an advantage to have extra thrust in control.

The coordinate systems including the world frame Aand the body fixed frame B are shown in Fig. 1. We useZ−X −Y Euler angles to define the Roll(φ), Pitch(θ) andYaw(ψ) in the local coordinate system. The rotation matrixfor the transformation from body fixed frame to the worldframe is given by:

ARB =

cψcθ − sφsψsθ −cφsψ cψsθ + cθsφsψ

cθsψ + cψsφsθ cφcψ sψsθ − cψcθsφ

−cφsθ sφ cφcθ

The linear accelerations in x,y and z directions can be

written as:

¨xdes = g(θdes cosψT +φdes sinψT ) (7)¨ydes = g(θdes sinψT −φdes cosψT ) (8)

¨zdes =1m

u1−g (9)

By applying PD controller to 7, 8 and 9 , we get,

¨xdes = xT + kd,x(xT − xcurrent)+ kp,x(xT − xcurrent) (10)¨ydes = yT + kd,y(yT − ycurrent)+ kp,y(yT − ycurrent) (11)¨zdes = zT + kd,z(zT − zcurrent)+ kp,z(zT − zcurrent) (12)u = mg+mzdes

= mg+m(zT + kd,z(zT − zcurrent)+ kp,z(zT − zcurrent))(13)

u represents the thrust applied by all the four motors ofthe quadrotor. The roll(θ ), pitch(φ ) and yaw(ψ) angles arecalculated as following:

φdes =1g(xdes sinψT − ydes cosψT ) (14)

θdes =1g(xdes cosψT − ydes sinψT ) (15)

ψdes = ψT (t) (16)

The subscripts T, des and current denote given trajectory,desired and current states respectively.The values of roll(θ ), pitch(φ ), yaw(ψ) angles and the thrustwas calculated from the control equations. Pixhawk takes θ ,φ , ψ and thrust as inputs and achieves the desired control.

A. Trajectory generation

A 3 waypoints trajectory was given to the quadrotor.The time alloted to the trajectory was sufficient so thatthe quadrotor could follow it by implementing linear con-trol.Maneuvering of the quadrotor is achieved by changingthe angular velocities of the motors which result in theangular acceleration of the quadrotor about its principal axes.In Section III it was shown that φ ∝ y As the change inangular velocity of motors results in φ , the natural choice ofoptimal function is the fourth derivative of position(yiv) alsocalled as jounce or snap. Minimum jerk trajectories havebeen tried for quadrotor [7] but the optimization of inputparameters can be justified with a minimum snap trajectoryonly [8].The trajectory was written in piecewise polynomial, by en-suring that the trajectory between two consecutive waypointsis a minimum snap trajectory.

f (t) = min∫ t

0|x(iv)|2, |y(iv)|2, |z(iv)|2, |ψ|2.dt (17)

by Euler Lagrange method, the optimal function has tosatisfy the following condition:

∂L∂m− d

dt

(∂L∂ m

)+

d2

d2t

(∂L∂ m

)− d3

d3t

(∂L∂

...m

)+

d4

d4t

(∂L

∂miv

)= 0

(18)The optimal function, L = f (m, m, m,

...m,m(iv), t). f (t) is aseven degree polynomial. There are 8 unknown co-efficientsfor each segment, these co-efficients were solved by initialand final boundary conditions and equating the values till 6th

derivative of f (t) at the intersection of two segments.

B. Segment time optimization

As the quadrotor started, passed through a ring and thenstopped, our trajectory had 3 waypoints and 2 segmentedtrajectories. The time was initially alloted proportional tothe distance between waypoints.

Ti =wi+1−wi

k(19)

In the above equation, the value of k decided the speedof the trajectory. The given trajectory can be followed Thewaypoints were defined and the trajectory time was specified.This case allowed us to optimize the segment time allocation.The segment time(T1 and T2) were re-allocated by giving T1an additional time and subtracting same amount of time fromthe next segment.

T1new = T1 + t ′

T2new = T2− t ′

t ′ was iterated within a range of value which kept the speedof trajectory under 1m/s and the optimization parameter wasthe total distance traveled by quadrotor.

f (T1new,T2new) = mint

∑0(|x|+ |y|+ |z|) (20)

subject to conditions:

t ′ < T1

w2−w1

T1new,

w3−w2

T2new<= 1

The time was optimized only for trajectories with 2 seg-ments but trajectories with more segments can be optimizedif the segments are seperated in pairs.

IV. IMPLEMENTATION THROUGH ROS

The section describes the flight controller used in details.Communication by using ROS and implementation of thesame to follow a given trajectory is also mentioned.

A. Flight Controller- Pixhawk

Pixhawk is a powerful 32-bit ARM architecture basedmicro-controller having failsafe backup controller and ex-tensive memory. No special controller designing is requiredfor researchers concentrating on navigation control and pathplanning applications [16]. It is easy to stream data, toand from Pixhawk through MAVLink protocol using Robot

Operating System (ROS), [17], due to availability of theprecompiled packages such as MAVROS.

The MAVLink protocol is also supported in the formof MATLAB packages enabling a direct control of thequadrotor, Fig. 8 shows the proposed forms of data flowfor Pixhawk.

GroundcontrolROS

Flightcontrol unitPixhawk V2PX4

Motorcontroller

Resultanttrajectory

MotioncaptureVICON

ControllerTrajectorygenerator

(x,y,z)des

(x, y, z)des

(x,y,z)current(x, y, z)current

φ ,θ ,ψThrust

Serially communicatedMAVLink messages

using USB to TTL cable

Fig. 8: Proposed Experimental Setup

B. Sensors and Feedback

The pixhawk flight controller is equipped with advancedmultiple sensors to enable accurate pose estimation of thequadrotor. It employs homogeneous as well as heterogeneousfusion of sensors to make the resultant data more dependableand accurate. There is homogeneous fusion amongst thetwo gyroscopes and two accelerometers provided and aheterogeneous fusion amongst all 3-axis gyroscopes, ac-celerometers, magnetometer and with single axis barometerto yield a 10 DOFs Inertial Measurement Unit (IMU). Thetwo accelerometers and gyroscopes also provide Pixhawkwith failsafe capabilities.

C. Offboard control using ROS

A ROS network consisting of the following systems wassetup using ’MAVROS’ & ’vicon bridge’ packages of ROSas shown in Fig. 10.

1) Sensor Data (from mavros package)2) Controller (Roll-Pitch-Yaw-Thrust control)

Fig. 9: Quadrotor with reflective IR markers(left) and objectcreated in VICON environment(right)

Fig. 10: Graph showing communication between the ROSnodes

3) Motion Capture feedback (vicon bridge)The VICON motion capture system (MOCAP) uses re-

flective markers to capture the locations. The Tracker 2.2software used allowed us to use multiple markers collectivelyto make-up object(s) in order to track the pose of desiredbody accurately. The pose estimate was calculated as aweighted mean of the MOCAP and the internal IMU data.RPYT control was adopted to achieve a desired pose. Thepresent and desired pose was known, thus establishing aclosed loop PID control over its pose. The communicationbetween the ROS computer and Pixhawk was first attemptedusing 433 MHz serial radio which showed latency in datatransfer. Hence, a wired mode of communication using USBto TTL cable was implemented. The Fig. 10 shows that viconMOCAP data was subscribed (received) by MAVROS usingthe /mocap/pose topic that enabled the fusion of the internalIMU and external MOCAP feedback. The offboard controllernode (C++ code run in ROS) published (sent) attitude andthrottle control over the setpoint attitude topic. Fig. 9 showsthe markers mounted on quadrotor and the markers detectedin Tracker 2.2 using VICON motion capture system.

V. RESULTS AND DISCUSSIONS

The results obtained by the experimental setup are dis-cussed in the following section. The plots of expectedtrajectory and the actual trajectory are also shown in thesection.

A. Values of Kt and Km

The plots of Kt and Km against the square of the rpm ofthe motor is shown in Fig. 11 and Fig. 12. The plots clearlyshow that the thrust and the reaction moment are proportionalto the square of angular velocity. This plot helps in directlycalculating thrust or moment if the rpm of the motors isknown.

B. Values of Ixx, Iyy and Izz

The values of the moment of inertia about x-axis, y-axisand z-axis calculated with the test rig and CAD model arecompared below.

Fig. 11: Plot of Thrust vs square of Angular Velocity (ω2)

Fig. 12: Plot of reaction moment vs square of AngularVelocity (ω2)

Test rig, kg-m2 CAD model, kg-m2

Ixx 0.0157 0.01Iyy 0.0134 0.011Izz 0.022 0.021

The values of Ixx and Iyy in CAD model are less than the testrig values and that can be expected due to the unaccounteddrag forces acting on the quadrotor. The results show that theactual angular acceleration will be less than the calculatedangular acceleration if the inertia is measured neglecting dragforces.The difference in value will increase as the size ofquadrotor increases. Izz on other side remains same in bothmethods. So, it can be concluded that the results obtainedfrom the test rig are valid and using test rig is a better practiceto measure inertia.

C. Trajectory segment time allocation

After the time alloted to each trajectory was optimised itwas observed that the quadrotor traveled less distance thanbefore. The paths are shown in fig. 14. The blue trajectoryis a distance proportionate time alloted trajectory while thered plots are the trajectories with each iteration tried. Theoptimising parameter was the total distance traveled by thequadrotor. The plot in Fig. 14 shows the change in optimisingfunction with iterations.

D. Trajectory traveled by the quadrotor

We were able to make the quadrotor follow a certaintrajectory by giving RPYT as inputs to the flight controller.The desired path and the path traveled by the quadrotor iscompared in Fig. 13. The Fig. 15 shows the composite image

of a quadrotor following the trajectory. The black cross marksare the waypoints in xy plane.

Fig. 13: Desired trajesctory and actual trajectory traveled bythe quadrotor

Fig. 14: The paths with iterations in t’ and plot of optimisedfunction vs iterations

Fig. 15: Composite image of a single quadrotor travelingthrough given trajectory

VI. CONCLUSION AND FUTURE WORK

In this paper we described methods to accurately mea-sure the physical parameters that play an important role indynamics. The methods mentioned are cost effective andensure less errors. We also described trajectory generation &segment optimisation for a trajectory with 3 waypoints. Wewere successful in commanding a minimum snap trajectorythrough ROS by providing Roll, pitch and yaw angles andthrust value.We are currently extending our methods of trajectory op-timisation to trajectories with more segments. We are alsoexploring the firmware provided so that we can implementnon linear control of the quadrotor in order to performaggressive maneuvers.

REFERENCES

[1] Inkyu Sa and Peter Corke, ”Estimation and Control for an Open-Source Quadcopter” in Proceedings of Australasian Conference onRobotics and Automation, Dec, 2011

[2] Ryan, A., Hedrick, J. ”A mode-switching path planner for UAVassistedsearch and rescue” in 44th IEEE Conf. Decision and Control, 2005European Control Conference, CDC-ECC 05, Seville, Spain, 2005.

[3] Alexis, K., Nikolakopoulos, G., Tzes, A., Dritsas, L. ”Coordinationof helicopter UAVs for aerial forest-re surveillance, in Applications ofintelligent control to engineering systems”, Springer, The Netherlands,2009.

[4] Randal W.Beard, ”Quadrotor Dynamics and Control.”, February, 2008.[5] Jong Tai Jang et.al ”Trajectory Generation with Piecewise Constant

Acceleration and Tracking Control of a Quadcopter”, in 2015 IEEE,[6] ”Trajectory generation and tracking using the AR.Drone 2.0 quad-

copter UAV”, in 12th Latin American Robotics Symposium and 2015Third Brazilian Symposium on Robotics, 2015

[7] Jing Yu, Zhihao Cai and Yingxum Wang ,”Minimum Jerk TrajectoryGeneration of a Quadrotor Based on the Differential Flatness”, in IEEEChinese Guidance, Navigation and Control Conference, 2014.

[8] Daniel Mellinger and Vijay Kumar, ”Minimum Snap Trajectory Gen-eration and Control for Quadrotors”, in IEEE International Conferenceon Robotics and Automation 2011, Shanghai, China

[9] J. Leishman. ”Principles of Helicopter Aerodynamics (CambridgeAerospace Series)”. Cambridge, MA: Cambridge Univ. Press. [On-line]. Available: http://books.google.com.au/books?id=nMV-TkaX-9cC

[10] S. Shen, N. Michael, and V. Kumar. ”Autonomous multi-oor indoornavigation with a computationally constrained MAV” in Proc. of theIEEE International Conference on Robotics And Automation, pages2025, Shanghai, China, May 2011.

[11] S. Shen, Y. Mulgaonkar, N. Michael and V. Kumar. Vision-based stateestimation and trajectory control towards high speed flight with aquadrotor.

[12] Ahmed Hussein, Abdulla Al-Kaff, Arturo de la Escalera and Jos MaraArmingol Intelligent Systems Lab (LSI) Research Group UniversidadCarlos III de Madrid (UC3M), Leganes, Madrid, Spain. AutonomousIndoor Navigation of Low-Cost Quadcopters

[13] Hyunsoo Yang and Dongjun Lee, ”Dynamics and Control of Quadrotorwith Robotic Manipulator”, in IEEE International Conference onRobotics & Automation (ICRA) ,Hong Kong, China, 2014.

[14] Xiang He, Zhihao Cai and Ruyi Yan, ”A Quadrotor Helicopter Local-ization Method Using 2D Laser Scanner in Structured Environment”,2013

[15] Yushu Yu, Xilun Ding. ”A Quadrotor Test Bench for Six Degree ofFreedom Flight” in Journal of Intelligent Robotic System, 2012.

[16] Meier, Lorenz, et al. ”Pixhawk: A system for autonomous flightusing onboard computer vision.” in IEEE international conferenceon Robotics and automation (ICRA), 2011.

[17] http://www.ros.org/