Design and Development of an Indoor UAV

Muhamad Azfar bin Ramli, Chin Kar Wei, Gerard Leng

Aeronautical Engineering Group

Department of Mechanical Engineering

National University of Singapore

Abstract

The primary objective of this project is to analyse the aerodynamics and propulsion

performance and also to design a control system of a semi-autonomous controlled UAV

that is able to conduct a reconnaissance mission in an indoor environment within a

building. The platform is aided by a collision avoidance system (CAS) to ensure safe

operation within the indoor environment.

This paper will begin by discussing the operations requirements of a UAV in an indoor

environment, followed by the selection of the flying platform and required components.

The basis of selection and the criteria will be discussed. This paper will also study the

aerodynamics and propulsion of the UAV and how it is affected by the indoor

environment. The control architecture of the modified UAV and the development of the

CAS will also be presented.

1) Introduction

A UAV can be described as a smaller scale aerial vehicle which is able to sustain stable

and controllable flight operations by its control system which can be pre-programmed to

follow a certain flight path or remotely-controlled from a ground station, without a pilot

on-board the aircraft. It has the advantage of saving labor cost and reducing need of

placing human life in risky situations. One of its many applications is to conduct

unmanned reconnaissance and surveillance mission whereby human presence or

intervention is undesirable.

In the context of outdoor application, the aircraft has more options to evade obstacles and

avoid collisions because there is less space constraint. It can also utilize GPS to enable

autonomous flight following pre-planned flight path and thus provide more control over

flight destination.

In an indoor environment, however, weak reception of GPS signals and limited space

which restricts the avoidance options have posed additional challenges to the operations

of the UAV. Moreover, due to size constraints, payload capabilities are also diminished

and the UAV can only carry minimal amounts of payload in order to achieve the mission

objectives. It is therefore important to study the effects of indoor aerodynamics on the

stability of the UAV and how small-scale sensors can be used to improve visibility of the

environment to ensure safe operation.

2) Indoor Operations Requirements

In an indoor environment, the common flight terrain in which the UAV may encounter

are mostly enclosed space, doorway, narrow corridor and staircase, while the common

obstacles are walls, ceiling, columns, furniture and people and other miscellaneous

objects. For the purpose of this project, we will focus only on the first three types of

terrains and the first three types of obstacles.

In an enclosed space, for example in a four-wall bounded room, the UAV must be able to

avoid colliding into walls, ceiling and columns present in the room. This mean it must be

able to maintain a safe distance between itself and the wall, at the same time maintain a

safe altitude, and also is able to evade columns successfully.

As the width of a typical doorway is about 100cm, thus the maximum length of the UAV

must be smaller than 80cm. For narrow corridor, the UAV should not be confused by the

smaller clearance on both of its sides and still be able to maintain straight path along the

corridor.

Other than space constraints, the indoor air is also not totally stagnant. There are still

risks of flow disturbances which will affect the control and performance of the UAV.

Some examples of sources of disturbance are the fans, air-conditioner blower, ventilation

shaft as well as external wind flow. To better appreciate the level of disturbance, we

carried out measurement of wind speed using a Testo Term 440 anemometer:

To ensure optimum performance of the UAV, it should either be able to counteract the

disturbance or avoid flying near the source of disturbance. We measured the wind speed

values from four sources of disturbance that are commonly found in an indoor

environment namely external wind draft from windows, draft from fans and draft coming

from an aircon ventilation shaft.

Figure 2.1 : Experimental set-up of wind speed measurement

Wind speed from a table fan

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7

0 0.5 1 1.5 2 2.5 3 3.5

distance from object (m)

Win

d sp

eed

(m/s

)

Figure 2.2: Results of wind speed measurement

In summary, we have discovered that the wind speed values from fans are the highest

averaging at 3.6 m/s and continue to affect the air around it for at least 3m away from the

source at a speed of about 1 m/s.

Figure 2.3: Ventilation shaft

Maximum recorded Wind speed from a ventilation shaft

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1

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3.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Distance away from disturbance

Win

d sp

eed

(m/s

)

Figure 2.4: Results of wind speed from a ventilation shaft

Air-conditioners and ventilation shafts do affect the air up to a range of 1 m., after which

the airspeed is not significant.

Wind speed in a HDB building corridor

0

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Storey

Win

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(m/s

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Maximum

Mean ( taken in1 min interval)

Figure 2.5: Wind speed measurement taken from a corridor on a windy day*

* Wind speed was taken at Block 354, Ang Mo Kio Ave 8

Wind speed from windows generally increase with the height from the ground and the

wind speed can go to a maximum of 4 m/s at higher storeys.

3) Overview of Project

From the selection criteria above, we have decided to select the Draganflyer V Ti as our

flying platform on which we will carry out our modifications in order to perform a

successful semi-autonomous reconnaissance flight mission in an indoor environment.

The following reasons are why this platform was finally selected out of various other

platforms.

Figure 3.1: The Draganflyer V Ti

The size of Draganflyer fits nicely with the specifications required in an indoor

environment. With an end-to-end diameter of 80cm, it fits nicely through doors and

corridors. Furthermore, even though the platform is generally small, the estimated

payload as suggested by the manufacturers is 100-300g which fits perfectly with our

payload demand of 200g.

However, there are also a few challenges that we foresee in choosing a flying platform

such as the Draganflyer. Firstly, the quad rotor design means that the Draganflyer needs

to use a non-linear control to achieve the required states of motion. However, since the

on-board electronics are already configured for flight, we do not have to worry about this

problem. However, the difficulty is in controlling the platform without adversely

affecting or making direct modifications to the on-board electronics. Attempting to

communicate with the complicated system as well interfacing our own control algorithms

with the on-board systems will also be a challenge in this project. The information on the

planned control architecture will be discussed in Chapter 5.

4) Aerodynamics and Propulsion

Due to the additional payload that is required to be carried by the Draganflyer, we are

therefore required to test the total thrust capabilities of the platform so as to ensure that

we are able to put on the additional payload of sensors, processors and camera whilst

maintaining stable flight. From the calculations and estimation of additional components

required, we estimate that we require a total payload of 178g in addition to its own

weight. The Figure below lists down the various components that are required to be

added to the platform in order for it to successfully complete its mission.

Component Weight(g)

Full Draganflyer set 484

BASIC Stamp module + programming board + additional sensors 75

PING sonar sensor 9

RF module 14

IR sensor x 4 20

Camera set 20

9 volt battery for camera and/or Stamp module 40

Total weight (Draganflyer + additional weight) 484 + 178 =

662g

Figure 4.1: Weight estimation of components required

Initial flight testing has been conducted in order to discover the total maximum thrust

capability of the Draganflyer. In order to obtain this thrust value, we conducted a simple

test in order to measure the force exerted. The following diagram shows the

experimental set-up: -

Figure 4.2: Experimental set-up for thrust measurement

1kg weight

Connected to ceiling

Measuring tape Spring balance

Figure 4.3: Picture of experimental set-up

A 1kg weight is tethered to the Draganflyer model in order to ensure that it does not fly

away when the rotors begin to spin. The initial weight of the Draganflyer including the

weight is recorded by the spring balance. The Draganflyer is then powered up and put to

maximum throttle. The difference in the weight is then recorded as the thrust provided

by the rotor blades.

It is well known that the thrust provided by the rotors is affected by the ground effect.

Due to the presence of the floor, the flow of air causes a high pressure region to develop

below the rotor blades. In order to measure the effect of the ground on the thrust

provided by the Draganflyer, a measuring tape is used to measure the height of the

Draganflyer above the ground.

Thrust vs height from ground

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Height from ground(cm)

Thru

st(N

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Figure 4.4: Results of thrust measurements

From the results, we can see that the thrust provided by the rotors is indeed affected by

ground effect up to a height of 1.2 m after which it remains relatively constant.

In order to measure effectively the total thrust provided in a stable hovering situation

which is not affected by ground effect, we now tested the Draganflyer thrust at full

throttle at a height of 1.77 m to discover the available effective thrust that it can take.

From the experiment conducted, the total measured thrust out of ground effect is 7.8 N or

780g. This shows that the platform is indeed suitable to carry out our required payload of

sensors.

Going upwards

Going downwards

In order to further view the effect of obstacles on the propulsion provided by the UAV as

well as the aerodynamic force exerted by the wall on the UAV, we modeled a simple

form of the Draganflyer by using Solidworks and used COSMOS Floworks to estimate

the forces on the model in an environment whilst varying the distance from the ground.

Figure 4.5: Velocity plot of Draganflyer at 30cm and 80 cm height.

Figure 4.6: Pressure plot of Draganflyer at 30cm and 80 cm height

Figure 4.7: Simulation of Flow trajectories of the Draganflyer

From the simulation, we have found that the thrust provided by the Draganflyer when it is

30cm from the ground is 7.5 N. The thrust then decreases to 6.87 N at 50cm and 5.78 N

at 60 cm. This indeed is consistent with our experimental results that the thrust generally

decreases as we move out of ground effect.

In conclusion, we have proved from experiment that the Draganflyer is indeed able to

carry the amount of payload necessary in order to implement the designed Collision

Avoidance System.

5) Control Architecture and Collision Avoidance System (CAS) Overview In order to preserve the Draganflyer in its original condition for future development, the

proposed control system is shown below, which does not require significant modification.

Figure 5.1: Overview of control system architecture As can be seen from Figure 5.1, the system consists of 3 microcontrollers as labeled. The

CAS consists of a microcontroller (labeled A), 4 infrared ranging sensors, a sonar sensor

B

Sensor data

Transmit sensor data via RF

Modified control

command transmitted to

receiver

Trainer port

Serial communication

Ground station

C

A

and a dual-axis accelerometer will be installed on-board the platform. All sensors data

will be sent via radio signal to a microcontroller (labeled B) on ground. After necessary

calculations and decision making, control command will be sent via serial

communication to another microcontroller (labeled C) for corresponding PWM pulse

generation, which the PWM signal will be sent to the on-board receiver through its

transmitter via trainer port connection.

Control algorithm

Figure 5.2: Control algorithm for indoor flight of Draganflyer

Initialization

Get sensor data

Stable? Stabilize

Obstacle behind?

Obstacle in front?

Obstacle on left?

Obstacle on right?

Move forward

Move forward

Move backward

Roll right

Loop

No

No

No

No

No

Roll left

Yes

Yes

Yes

Yes

Yes

Base on the algorithm, the microcontroller will always seek for sensors’ feedback on the

craft’s attitude, altitude and distance from possible obstacles to determine suitable control

actions.

Components selection To provide visibility of the environment, ranging sensors including laser, sonar and

infrared (IR) can serve the purpose. However, IR sensors were ultimately chosen because

of its low cost, light weight, and most importantly, unlike sonar, it does not give

erroneous result when it is sensing at an angle with target surface. To account for more

distance allowance, the desirable ranging distance is 2m. However, the best IR sensor

available is Sharp GP2Y0A02YK which has a reasonable ranging distance of 20cm –

150cm and each weighs only 5grams.

Figure 5.3: Sharp GP2Y0A02YK (left) and Parallax MEMSIC 2125 (right)

For tilting and stabilization control, a dual-axis accelerometer was used to obtain tilt

angle of the platform with respect to ground from its acceleration outputs of both X and

Y axes. MEMSIC2125 from Parallax was chosen because of the extreme light weight and

its simple code for obtaining acceleration and tilt angle hence lessen program runtime

which is significant during PWM generation.

For altitude control, Parallax’s PING))) sonar sensor was chosen because it requires less

output processing time as compared to IR sensor (the time criticality will be discussed

further in section “Signal update rate”). However, the payoff is it weighs 10grams. Since

the tilting angle of the Draganflyer will be set to be less than 10 degrees, hence the error

in readings would be insignificant.

Figure 5.4: Parallax’s PING))) Sonar sensor (left) and BS2sx microcontroller (right)

As for microcontroller, although not as cheap and large RAM capacity as PIC

microcontroller, Basic Stamp was chosen mostly because our lab has quite a large

amount of them and it is able to deliver to all our requirements. It can also be easily

interfaced with any computer via serial or USB port and is able to support serial and I2C

input. Most importantly, it can easily duplicate and generate the pulse signal from the

transmitter which has important application in this project. Besides, it is also widely used

in many robotics and RC applications and has forums which provide much

troubleshooting information.

Sensor Calibration Before putting into application, sensors need to be calibrated. Since the accelerometer

and the sonar sensor has already been calibrated by manufacturer for operating in typical

room temperature of 250C, and has also been verified to operate normally from

experiments, no further calibration is needed. However, due to the fact that the IR

sensor’s output is of non-linear relationship with the measured distance, proper

calibration is necessary. A calibration curve was produced from experiment based on the

guidelines provided by the distributor, Acroname [1] and was used to obtain several

calibration constants which will be used in the programming codes.

Distance measured vs ADC output

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8-bit ADC output

Dis

tanc

e, L

(cm

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1 / (L + k) vs ADC output with linear trendline

y = 0.00011614x + 0.00130556

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0 50 100 150 200 250 300

8-bit ADC output1

/ (L

+ k)

Figure 5.5: Calibration curves of Sharp GP2Y0A02YK IR sensor From the calibration curve, we obtained a linear relationship between the distance and the

Analog Digital Converter’s (ADC) output. From the trend line’s equation, 2 calibration

constants, m' and b', can be obtained from the slope and its intercept. The third constant,

k is a self-determined constant which was deemed to give the most accurate readings.

The calibration equation follows the linear equation format y = mx + c:

1 / (L + K) = m * (ADC output) + c After some manipulation, Distance, L = (m' / (output + b')) – k

where m'=1/m and b'=c/m

With the calibration constants, accurate readings can be obtained from the IR sensors.

Non-perpendicular sensing conditions

When the sensing surface is not perpendicular with the IR sensor, it gives slight error

from the actual distance. Figure 6.6 below shows measurement taken when sensor is at

certain angle with the sensing surface at a fixed distance of 50cm, using both horizontal

and vertical sensor mounting (mounting orientation w.r.t. ground). The results show that

vertical mounting gives less error over wide range of angle as compared to horizontal

mounting, with error ranging from 2cm at 10 degrees angle to 10cm at 80 degrees angle.

Figure 5.6: IR sensor sensing at various angles with respect to sensing surface with 2

different mounting Other than sensing at an angle with the sensing surface, sensing at corner will also bring

some error to the distance measurements. To identify the significance of the error,

measurements were done at known distance (50cm) and were compared with the readings

obtained. The measurements were done at two corner angles: 900 and 1100. Corners of

angle less than 900 are not considered as other two sensors at the sides will forbid the

Draganflyer from approaching that sharp corner.

Horizontal mounting

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Angle (deg)

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ActualMeasured

Vertical mounting

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Angle (deg)

Dis

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Figure 5.7: Corner measurement

The above results agreed with each other that vertical mounting is a better way for

mounting the IR sensors. The experimental studies also show that there is no problem

with the sensor detecting the floor while it is still on ground, thus the IR sensors will be

mounted vertically with respect to the ground.

PWM Signal Generation As the microcontroller will take over the transmitter’s role to generate control signal, it is

important to analyze the control signal used to control the Draganflyer to ensure that

correct signal is generated as compared to the original signal from the transmitter. The

analysis shows that the signal used is pulse width modulation (PWM) signal consists of 6

channels of pulse information which each represents command signals to the actuators.

As mentioned earlier, the Basic Stamp microcontroller has built-in command which

enables easy generation of PWM pulse by a simple PULSOUT command [2]. This

provides much convenience for generating the 6 channel pulse train of variable pulse

widths. The analysis also shows that the time span of pulse train is approximately 20ms.

Comparison between Horizontal & Vertical Mounting with Actual Measurements

0

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250

20 30 40 50 60 70 80 90 100 110 120 130 140 150

Distance (cm)

Dis

tanc

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m)

Corner angle: 90 deg

Comparison between Horizontal & Vertical Mounting with Actual Measurements

020406080

100120140160180

20 30 40 50 60 70 80 90 100

110

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Distance (cm)

Dis

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m)

ActualHorizontalVertical

Corner angle: 110 deg

The pulse width of each channel ranges from 0.6ms – 1.5ms, all of a magnitude of

approximately 4.2V. The neutral pulse width is about 1.05ms.

Signal update rate Due to the fact that the control signal generation is entirely on the hand of the

microcontroller (labeled C in Figure 5.1), the signal generation condition must be the

same as those from the transmitter. However, besides generating PWM signals, it also has

to receive control command from microcontroller B in order to generate the right pulse

width for each of the 6 channels.

Since each pulse train has a time span of 20ms, and each channel takes up 1ms – 2ms,

hence the only time left for the microcontroller to serial-in control command is only

about 9ms. This implies that the program code has to be kept as short as possible so that

the program runtime will not delay the signal update between the microcontrollers. Thus,

time is a critical issue, which is the reason why in previous section on selection of sensors

the output processing time is one of the important considerations. Many serial

communications between microcontrollers are involved in the proposed control system.

Hence, it is important to investigate the time needed for each serial communication.

Time vs Number of bytes Sent

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Tim

e (m

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Flow ControlWait method

Time vs Number of bytes Received

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Flow ControlWait method

Flow Control method: Time to Send vs Receive

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Wait method: Time to Send vs Receive

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Number of bytes

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SendReceive

Figure 5.8: Time needed for serial communication between microcontrollers Figure 5.8 shows that the time varies linearly with the number of bytes received (sent).

Also, the time spent is lesser if “Flow Control method” is used in which the sender waits

for the receiver to establish transmission connection, rather than “Wait method” in which

the receiver wait for the sender. However, flow control can only be established between

wired connections, we will still need to use “wait method” for wireless communication.

Besides, for “Flow Control method” every extra byte will require an additional time of

Receiving is 0.3ms faster than sending

Receiving is 0.2ms slower than sending

1.1ms; for “Wait method” every extra byte will require an additional time of 1.2ms. Also,

it is about 0.3ms faster to receive than to send.

For microcontroller C, since we have only about 9ms for serial communication, from

Figure 5.8 the maximum number of bytes allowed is 6 bytes. However, only 4 variables

which control the speed of 4 motors need to be sent and 2 other channels can be

neglected.

For microcontroller A and B, taking into account the time needed for both wireless and

wired serial communication, data collection and data processing, the program runtime

will definitely be more than 20ms. Hence, the fastest possible signal update rate will be

every 40ms, which is equivalent to a frequency of 25Hz.

6) Conclusion and current Progress of Project and future

From the data of the wind speed values measured, we will then verify the effectiveness of

the Draganflyer in withstanding the various airflow disturbances found. However, since

wind tunnel testing is most probably not possible given the lack of resources, we will

perform Computational Fluid Dynamics using available software to help us estimate the

drag forces experienced by the Draganflyer due to these disturbances. The Draganflyer

will first be modeled using Solidworks and then put under various ambient flow

conditions using COSMOS Floworks. In order to investigate the effect of walls and the

ground on the flow around the Draganflyer, we would also simulate this flow in the

software and obtain the results from the software. The results will then verify our

hypothesis that the Draganflyer is indeed able to withstand the various disturbances in the

air effectively in order to complete its reconnaissance mission.

We are also still currently in the progress of putting together the control architecture and

attempting to interface the communications between the BASIC stamp processor and the

transmitter module. Once this has been completed and the sensors have been placed on

board the Draganflyer, we would then proceed with validating the effectiveness of the

control algorithm through a series of flight testing.

- Ground Flight Testing

In order to prevent damage to the UAV system we have integrated, initial ground-based

flight testing will be done. This is done by running the Draganflyer while it is held on the

ground. Various objects are then placed near the sensors simulating obstacles around the

platform. We can therefore view how the platform reacts to each obstacle and adjust the

control algorithm in the case that any unwanted effects occur. After this preliminary

flight testing is done, we can therefore move on to actual flight testing within a closed

room in order to view the actual performance of the integrated system and whether it is

adequate to avoid the obstacles around it successfully.

7) Future Developments

The current configuration of 4 distance sensors is not adequate for the UAV to have

complete vision of its surroundings. However, the number of sensors allowable on the

platform as well as the complexity of the resulting algorithm prevents us from using more

sensors. Furthermore, the existence of more sensors means that the processor will take

even more time in order to make a decision when reacting to the various inputs thus

increase the lag time and therefore the resulting response time of the system. Due to time

and cost constraints, these objectives could not be met by our group.

We therefore recommend better and more sensors to be added to the flying platform.

Sophisticated vision based systems can be integrated together with the camera to allow

the UAV to better understand the obstacles surrounding it and react accordingly.

Possible future developments can even utilize a scanning device which is able to

construct a 3D image of the surrounding architecture that can be viewed by the UAV in

its current position and it can then map out a safe flight route or passage around the

obstacles and conduct the reconnaissance mission safely.

The current system also utilizes a ground based station that does the calculations for the

UAV as well as control the flight systems of the UAV directly. A better and more robust

solution would be to have all the flight computers on-board the platform itself. However,

this is again constrained by the inherent payload capability of the UAV itself. Further

aerodynamics wind tunnel testing can also provide better first-hand information in

measuring the aerodynamic capabilities of the flying platform when affected by the

various disturbances spelt out in this paper.

8) Acknowledgements We would like to thank our project supervisor A/Prof. Gerard Leng Siew Bing for

invaluable assistance and advice during the course of this project. We would also like to

thank DSO National Laboratories for sponsoring the cost of our project materials without

which we could not hope to successfully achieve the required objectives.