Free Flying Micro Platform and Papa-TV-Bot:
evolving autonomously hovering mobots

Stefan Marti
The Media Laboratory
Massachusetts Institute of Technology
20 Ames Street, Cambridge, MA USA 02139
stefanm@media.mit.edu

Notes: The author has written a more recent and extensive paper about FFMPs that includes this paper. There is also a website about a prototype. Back to the Free Flying Micro Platform (FFMP) and Papa-TV-Bot homepage.

Content

Abstract
1 Introduction
2 Scenario Papa-TV-Bot
3 Schedule
4 Basic technologies of vehicles of the Phases 1 through 3
4.1 Phase 1
4.1.1 Sensors and controlling
4.1.2 Propulsion
4.1.3 Batteries and power transmission
4.2 Phase 2
4.3 Phase 3
5. Summary
Acknowledgements
References
Footnotes


Abstract

This paper outlines the possibilities, the evolution, and the basic technical elements of autonomously hovering micro robots. It consists of three parts. The first part presents the application Papa-TV-Bot, a free flying automatic video camera. The second part is a schedule for the long-term development of autonomously hovering mobots1 in 8 phases. The third part describes the basic technologies of the vehicles of Phases 1 through 3.


1      Introduction

It is well known that entities heavier than air cannot stand still in the air without the help of propulsion engines. The only machines capable of free hovering are helicopters2 [45]. Their ability to move freely in 3-dimensional space [28] makes them important not only for transport but also for looking at the world from unusual viewpoints3. This is especially interesting for television and video productions. Aerial video- and photography is also conducted through unmanned vehicles, such as remote controlled helicopters (e.g., [3,11,17,44,47]). Although the size of these vessels is only about 3 to 5 feet in diameter, they are too dangerous for indoor use because of their large, exposed rotors. Additionally, most of them use noisy and grimy combustion engines. Due to their underlying mechanical principles, they are fundamentally unstable with highly nonlinear dynamics [28,23,24].

For these reasons, aerial photography using model helicopters is limited to expert pilots in outdoor environments, and cannot be conducted near or over crowds of people. Nevertheless, these camera positions would be interesting for TV productions [33] of entertainment shows like concerts and sports events. Cameras hovering over an open field, taking shots from directly above the audience, could convey thrilling pictures. Another interesting domain for these vehicles would be hazards of all kinds, such as radiated areas, hostage situations, and structurally unstable buildings into which it is too dangerous to send humans.

In the first part of this paper, I present a scenario with a Papa-TV-Bot. The second part is a schedule for the long-term development of autonomously hovering mobots in 8 phases, starting with a simple Free Flying Micro Platform (FFMP), developed into a Papa-TV-Bot, then into a hyper-intelligent zero-gravity mobot with multi-ethical awareness. In the third part, I describe the basic technologies of a vehicle of the first three phases, the Free Flying Micro Platform (FFMP), in more detail. It is a Micro Air Vehicle (MAV, [58,35]), "a tiny, self-piloted flying machine," neither bird nor plane, but "it's a little of both with some insect and robot characteristics thrown in" [48]. Therefore, compared to today’s R/C helicopters [25] it is smaller (diameter less than 10 inches), quieter (electro motors), safer (rotors hidden in the fuselage), and—most important—it can hover automatically.


2      Scenario Papa-TV-Bot

How does the world look through the eyes of a humming bird? Imagine a basketball game: You watch the players from an altitude of twenty feet and then—within seconds—see them from three inches above the court floor. Then you follow the player with the ball across the whole court, always exactly one foot above his shoulder. You pass him and climb up quickly to one inch above the basket, right in time for the slam. The device that could deliver these unusual camera perspectives is a 5-inch autonomous rotary-wing MAV with a video camera and wireless transmission. Four electric ducted fans and an absolute position sensor enable it to hover automatically. After it is switched on, the mobot automatically stabilizes itself in the air, so that it stays where it was put. To move it away from this initial position, one can use simple voice commands such as up, down, left, and right, spoken directly towards the vehicle, or through a walkie-talkie-like communication device. It also accepts more complicated verbal mission requests like "Follow this person at a distance of 8 feet and an altitude of 5 feet." Because such a video surveillance activity resembles Paparazzi photographers, the appropriate name for this device is Papa-TV-Bot: Paparazzi Television Mobot. To reduce the annoying effects of such a "flying spy camera," another set of intuitive voice commands, like go away, let it immediately move away from the speaker. Additionally, it must
  • Avoid obstacles. If a human or non-human object obstructs the MAV during its filming missions, it must try to fly around it (e.g., [18]).
  • Evade capture. Due to its purpose of approaching objects very closely and flying over crowds of people, it has to evade somebody trying to catch it.
  • Be Safe. Because a Papa-TV-Bot is supposed to operate above people, it has to have extensive safety mechanisms. In case of failure of engines or electronics, or if the remote emergency kill-switch is pressed, four gas filled airbags are inflated instantaneously and cover most of the surface of the inoperational vessel. Equipped with these protective airbags, it falls back to earth without causing any harm.

3      Schedule

In order to reach the sophisticated level of a Papa-TV-Bot, I propose to develop and evolve autonomously hovering mobots gradually. For this purpose, I have defined 8 distinctive phases. In each phase, certain features and abilities are added to the characteristics of the previous phases:
  • Phase 1: Free flying micro platform (FFMP) for studying helicopter control, automatic control systems, and automatic hovering.
  • Phase 2: Flying camera: for indoor aerial video, and fast and uncomplicated Electronic News Gathering (ENG) tasks.
  • Phase 3: Listening mobot: direct voice communication with a mobot.
  • Phase 4: Mobot with crude situational awareness through its sensors, good for more complex ENG tasks. Due to their autonomy, several mobots per cameraman are possible.
  • Phase 5: Mobot that understands complex spoken language and has refined situational awareness: intelligent autonomous micro video camera with maximum degrees of freedom.
  • Phase 6: Mobot that learns from experience: the longer it operates, the more efficiently it behaves.
  • Phase 7: Self-repairing mobot, or mobots being able to repair each other.
  • Phase 8: Truly intelligent and highly responsible mobot.
Table 1 outlines the main goals, primary motivations, as well as the important domains of each phase.




Table 1. The 8 Phases for developing autonomously hovering mobots.
Phase
Main goal
Primary Motivations
What is it good for
Domains
1
 Standing still in air with automatic self stabilization Building a small (< 10 in) and quiet (< 70 dBA) entity, which is able to stay still in the air, stabilize itself automatically, and move in three-dimensional space. Make it as autonomous as possible. Free flying micro platform (FFMP) for studying helicopter control, automatic control systems, and automatic hovering.
Mechanical engineering
Electrical engineering
Aerial robotics
Micro Air Vehicles
Micro Modeling, Indoor Flying
2
 Passive vision Adding a wireless camera for conveying pictures from otherwise impossible camera positions, e.g., close above crowds of people, as well as complex camera movements like fast and seamless camera travels through narrow and obstacle rich areas. Flying camera for indoor aerial video, and fast and uncomplicated Electronic News Gathering (ENG) tasks.
Aerial video and photography
AV technology
Electronic News Gathering (ENG), Video and TV productions
3
 Simple listening capability Making it respond to simple verbal requests like Up! Down! Turn left! and Zoom in! Listening mobot: direct voice communication with a mobot.
Speech recognition
4
Active vision
Simple tasks
Simple morality
Adding sensors to improve its perception of the environment for human and non-human obstacle avoidance, as well as for evasive behavior
Making it able to understand and carry out tasks like Come here! and Leave me alone!
Implementing simple moral prime directive Do not harm anybody or anything
Mobot with crude situational awareness through its sensors, good for more complex ENG tasks. Due to its autonomy, several mobots per cameraman are possible.
Sensing technology
5
 Complex tasks Adding more vision and natural language understanding to make it behave like an artificial pet; understanding complex verbal requests like Follow me! Follow this man in a distance of 5 meters! Give me a close up of John! Mobot that understands complex spoken language and has refined situational awareness: intelligent autonomous micro video camera with maximum degrees of freedom.
Vision processing
Natural language processing
6
 Adaptation to environment, emergent robotic behavior Creating an adaptive, behavior-based autonomous mobot, which learns from interaction with the environment about dangerous objects and situations, as well as about its power management and flying behavior. Mobot that learns from experience: the longer it operates, the more efficiently it behaves.
Artificial life, Adaptive behavior
Genetic Algorithms, Classifier Systems, Genetic Programming
7
 Use of tools Modifying it so that it can use external physical tools for simple self repair and self reproduction Self-repairing mobot, or mobots being able to repair each other.  
8
Intellect
Cross cultural morality
Improving the intelligence up to Artilect stage (artificial intellect, ultra-intelligent machine)[14,26]
Connecting an Artificial Multi Ethical Advisor System (AMEAS, Cross Cultural Ethical Knowledge) to make sure its behavior is always ethically correct [32]
Truly intelligent and highly responsible mobot Note that [14] expects such devices realized within two human generations.)
Neuro Engineering
Philosophy, ethics; expert systems


4 Basic technologies of vehicles of the Phases 1 through 3

4.1      Phase 1

The FFMP of Phase 1 is appropriate for studying helicopter controls, automatic control systems, and automatic hovering. The vessel is supposed to be simple: it mainly consists of 4 micro electric ducted fans and an absolute position sensor.
4.1.1      Sensors and controlling
The main goal of a vehicle of Phase 1 is the ability to hover automatically. The problem of automatic hovering has been addressed by many research projects (e.g., [5,7,28,49]). Most of these projects use inertial sensors like accelerometers and gyroscopes [12]. However, "inertial sensor data drift with time, because of the need to integrate rate data to yield position; any small constant error increases without bound after integration" [6]. Additionally, the size of these sensors limits further miniaturization of the vehicles, which is crucial for the unobtrusiveness of a MAV. On the other hand, absolute position sensing has made much progress lately (e.g., [12,55]). Due to the high accuracy, low latency, and small size of these sensors, I think it is possible to build a simple MIMO control system for automatic hovering that no longer depends on the measurement of accelerations, be they translational or rotational. A self-stabilizing system, based only on absolute position sensing, would decrease the complexity of the control system remarkably. The idea is that the rotational movements of the longitudinal (roll) and horizontal axis (pitch), which are usually detected by gyroscopes, could also be detected indirectly through the resulting translational movements (forward/backward, left/right). If a rotary-wing vehicle tilts forward (rotational movement), it automatically and instantaneously initiates a linear forward movement. On the other hand, if a control system can limit the linear displacement of a flying mobot to a minimum, horizontal and longitudinal angular movements should automatically be under control too. First, it must be determined whether sensing linear displacement indeed is sufficient to keep a MAV in horizontal balance. However, given the relatively small size and low price of commercially available absolute position sensors on a radio4 or ultrasonic basis (e.g., [13]), such a construction would be an elegant solution to the automatic hovering problem5. An additional heading sensor (magnetic compass) might be necessary for controlling the movements around the vertical axis6. However, it has to be mentioned that external active beacons, which are used by most absolute position sensors for the trilateration or triangulation process, conflict with the initial idea of complete autonomy of a flying mobot. Therefore, other sensing technologies and controlling concepts (like on-board vision) might be considered for mobots of later phases7.
4.1.2      Propulsion
I propose the use of micro electric ducted fans [38,57]. They are less efficient than conventional rotors, but the main advantage of ducted fans is that they are hidden in the fuselage. This means that they protect the operator, nearby personnel, and property from the dangers of exposed rotors or propellers, which is particularly important for indoor MAV. As [1] points out, ducted fan design provides a number of additional advantages, such as reduced propeller or fan noise, and elimination of the need for a speed reducing gear box and a tail rotor. Furthermore, electric ducted fans are quieter than combustion engines [29]. An alternative to the ducted fan would be the much more efficient Jetfan [20]. However, this technology is not yet available in the requested small size.
4.1.3      Batteries and Power Transmission

Although using electric motors for propulsion leads to a relatively quite MAV, it has a major disadvantage: compared to fossil fuels, batteries have a low energy density. Therefore, the weight of electric R/C helicopters is much higher than the weight of models with combustion engines. This leads to short free flight performance times: commercially available electric model helicopters only fly for 5 to 15 minutes8 [25]. Since the battery will be the heaviest part of an electric MAV, it is imperative to use the most efficient technology available, such as rechargeable solid-state or thin-film Lithium Ion batteries (Li+). They have the highest energy density among commercially available batteries (83 Wh/kg), more than twice that of Nickel-Cadmium (NiCd, 39 Wh/kg). Other technologies are even more efficient, like Lithium Polymer (LiPoly, 104 Wh/kg) and the non-rechargeable Zinc Air (ZnAir, 130 Wh/kg). However, these have other drawbacks (e.g., low maximum discharge current) [43], or are not yet available [31,53].

Another possibility to consider for earlier phases is tethering the mobot to batteries on the ground with an "umbilical cord." This would enable virtually unlimited performance times, at the expense of range and flexibility. Wireless Power Transmission [36] would be interesting, but is not an issue yet9.

4.2      Phase 2

The vehicle developed in Phase 2 is an FFMP (Phase 1), but with the additional functionality of a Flying Camera. Such a vehicle could be used for indoor aerial video and simple Electronic News Gathering (ENG) tasks for live coverage. There is no video processing required in Phase 210; therefore, the only additional elements are a micro video camera and a wireless video transmitter. Given the limited payload capability of a MAV, the main selection criteria are weight and size. Fortunately, there is a variety of commercially available devices which could meet these criteria. Table 2 lists three possible cameras, Table 3 three transmitters.



Table 2. Micro Video Cameras.
type manufacturer size weight chip horizontal resolution pixels
PC-17YC [41] Supercircuits 1.6x1.6x2.0 in 2.5 oz CCD 1/3 in color 450 lines (> S-VHS) 410,000
MB-750U [34] Polaris Industries 1.5x1.5x0.9 in 0.9 oz CCD 1/3 in color 420 lines 251,900
PC-51 [42] Supercircuits 0.6x0.6x1.4 in 0.3 oz CMOS 1/3 in b/w 240 lines (< VHS) 76,800



Table 3. Wireless Video Transmitters.
type manufacturer size weight range frequency output
VidLink 100 [56] Aegis 1.1x0.8x0.4 in N/A 500–2500 feet 434 MHz 100 mW
MP-2 [37] Supercircuits 2.0x1.3x0.2 in 0.5 oz 700–2500 feet 434 MHz 200 mW
VID1 [54] Spymaster 0.6x0.9 in N/A 1000–2000 feet 434 or 900 MHz 80–250 mW




4.3      Phase 3

The vehicle developed in Phase 3 is an FFMP (Phase 1) with Flying Camera functionality (Phase 2), but additionally a Listening Mobot, with which direct voice communication in 3D space is possible. The main motivation is to communicate with an autonomous mobot in natural language [50,46]. Natural language access to autonomous mobots has been studied in detail in the context of land-based robots [30], but not for hovering mobots. Because such a vehicle is supposed to stabilize itself automatically, the movements of the platform should only be controlled by high level spoken commands such as go up and turn left. These commands describe only relative movements. The actual control of the speed of the fans should be performed automatically by the MIMO system. I suggest 4 categories of speech commands in Phase 3:

  • linear movements: up, down, left, right, forward, backward
  • turning: turn left, turn right
  • amount: slower, faster, stop
  • camera related: zoom in, zoom out11

Michio Sugeno of the Tokyo University of Technology has built a helicopter [49,21,22,23,24] that is eventually supposed to accept 256 verbal commands, such as fly forward, hover, fly faster, stop the mission and return. "Tele-control is to be achieved using fuzzy control theory. Ultimately, our helicopter will incorporate voice-activated commands using natural language as 'Fly forward a little bit.' The idea is that a relatively inexperienced remote operator can use natural language voice commands rather than a couple of joysticks that may require months of training. These commands are naturally 'fuzzy' and hence fit into the fuzzy logic framework nicely" [49]. Although the controlling concept is interesting, this helicopter cannot operate indoors; with its overall body length of 3.57m, it is far away from the size requirements of a MAV of Phase 3.

For the same reasons, I suggest using outboard processing of language in Phase 3. Verbal commands are spoken into a microphone that is connected to a standard speech recognition system (e.g., [2,19]). The output is fed into the MIMO system.



5      Summary

This paper outlines the possibilities, the evolution, and the basic technical elements of autonomously hovering micro robots.

First, the paper describes the application Papa-TV-Bot: an autonomously hovering mobot with a wireless video camera. This vessel carries out requests for aerial photography missions. It can operate indoors and in obstacle rich areas, where it avoids obstacles automatically. This rotary-wing micro air vehicle (MAV) follows high level spoken commands, like follow me, and tries to evade capture.

In part two of the paper, a schedule for evolving a simple Flying Micro Platform (FFMP) to a Papa-TV-Bot is shown. In even later phases of the schedule, the mobot is supposed to understand complex spoken language such as "Give me a close up of John Doe from an altitude of 3 feet" and has refined situational awareness. Furthermore, it learns from experience, repairs itself, and is truly intelligent and highly responsible.

In the last part, a description of the basic technical elements of an FFMP is given; sensors, propulsion, and batteries are discussed in detail. A simple absolute position sensor and four micro ducted fans are the main components of an FFMP of Phase 1. A micro video camera and a wireless transmitter are added in Phase 2. Speech recognition for high level control of the vessel is implemented in Phase 3.



Acknowledgments

I would like to thank Jane Dunphy for supporting me with very useful advice on how to write a paper, as well as Dave Cliff for the inspirations that I got from his Embodied Intelligence lecture. Furthermore, I would like to thank Gert-Jan Zwart† (1973-1998) for all the discussions we had. Your ideas will never die.


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  58. What are Micro Aerial Vehicles? (1998, March 24) [WWW Document]. URL http://www.aero.ufl.edu/~issmo/mav/info.htm (visited 1998, May 7).
  59. World record with an electric helicopter [WWW Document]. URL http://www.ikarus-modellbau.de/eecowr.htm.


Footnotes

  1. The expression mobot is defined as "small, computer-controlled, autonomous mobile robot” [51].
  2. Except for VTOL [39] and tiltrotor airplanes [52].
  3. Other domains for these vehicles would be hazards of all kinds, such as radiated areas, hostage situations, and structurally unstable buildings, into which it is too dangerous to send human, as well as search & rescue, surveillance, law enforcement, inspection, aerial mapping, and cinematography [3].
  4. [12] mention that "according to our conversations with manufacturers, none of the RF systems can be used reliably in indoor environments.” (pp. 65)
  5. Note that GPS is not an option, both because it is not operational indoors and its accuracy is not high enough for our purpose (even with DGPS).
  6. Another possibility would be to use three absolute position sensors instead of one.
  7. "A truly autonomous craft cannot completely rely on external positioning devices such as GPS satellites or ground beacons for stability and guidance. It must sense and interact with its environment. We chose to experiment with on-board vision as the primary sensor for this interaction” [3].
  8. The current world record is 63 minutes [59].
  9. Important research was conducted in the context of a microwave-powered helicopter that would automatically position itself over a microwave beam and use it as references for altitude and position [8,9,10].
  10. Only Phase 4 might use the video image for obstacle avoidance.
  11. [16] even use speech recognition to tilt the camera of their commercial aerial photography HiCam helicopter.





I wrote this paper as a final project for MIT class 6.836 Embodied Intelligence, as well as for MIT class 21F.225 Advanced Workshop in Writing for Science and Engineering, during May 1998.

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Send me some comments! Stefan Marti Last updated May 24 1998.

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