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Towards a Robotic Ecology
BriefingAugust 27, 1999
Rodney Brooks Greg Pottie (MIT) (UCLA)
ISAT DARPA2
Robot Ecologies
Where we are: Single robot that has as its intellectual metaphor a lone animal that perhaps can interact with people.
Where we are going now: Swarms of identical robots based on social insect metaphors, perhaps with augmented communication.
Where we want to go: Self deploying, and self sustaining ecologies of plant-like robots and animal-like robots that symbiotically interact across many species, in order to carry out complex missions without logistical support.
ISAT DARPA3
The Robot Ecologists
• Rod Brooks, ISAT
• Greg Pottie, UCLA
• Dick Urban, DARPA
• Elana Ethridge, SPC
• Polly Pook, IS Robotics
• Sarita Thakoor, JPL
• David Gerrold, writer
• Russ Frew, ISAT
• Al McLaughlin, ISAT
• Chuck Taylor, UCLA
• Maja Mataric, USC
• Brian Wilcox, JPL• Paul MacCready,
AeroVironment• Doug Stetson, JPL,• Helen Greiner, IS Robotics,• Ian Waitz, MIT• Dave Shaver, Lincoln Lab• Steve LaFontaine, MIT• Steve Leeb, MIT• Erik Syvrud, OST• John Blitch, DARPA• Mark Swinson, DARPA• Bob Nowak, DARPA• Keith Holcomb, Marines (ret)
COMMITTEE ITINERANTS GUEST PRESENTERS
ISAT DARPA4
Warfare in an Asymmetrical Situation
• Stay outside of detection circle depends on cross section (self)
• Within circle want to: sense what is happening maintain long term presence tag things and infiltrate surgically
and outfiltrate(!) maintain covertness
• Stay outside of lethality circle depends on weapons (of
opponent)
• Want numerical advantage• Within circle want to:
sense what is happening provide targeting information disrupt the opponent’s cohesion
and will
SURVEILLANCE ENGAGEMENT
peoplerobots
detection/lethality circle
The game is changing--we must change our response.
Logistics chain
ISAT DARPA5
Why Using Robots Is Hard, Yet Good
• Need covert deployment• Need occasional mobility• Need long term operation
energy supply logistics possibly resupply (bio
sensors)
• Need covert information return
• Robots can move• Robots can be very small• Robots can carry variety of
sensors• Robots wait patiently
SURVEILLANCE ENGAGEMENT
• Need rapid deployment• Need rapid mobility• Need logistics chain• Need reliable, rapid
information processing and transmission
• Need active responses
• Robots can move• Robots are expendable• Robots can carry a variety of
sensors• Robots can provide many
viewpointsWe know where you are and what you are doing.
ISAT DARPA6
Solution: The Robot Ecology
• Build an ecology of ‘animal’- and ‘plant’-like robots Go beyond the idea of single mobile robots
Develop the collective as a super-organism where no single part understands the whole
• The Robot Ecology is a self-constructing infrastructure
supports diverse individual tasks and enables more complex missions
handles system degradation gracefully
is self-sustaining throughout mission life
ISAT DARPA7
How The Components Combine
caterpillar (mobile sensor)
stationary sensor mother plant
“seed” sensors
ISAT DARPA8
What new capabilities?
• Precondition the battlefield for timely and precise targeting of enemy assets Know the environment
• scout, search, collect, penetrate, filter, report Tag enemy assets
• reduce fog; trace and target Weaken enemy infrastructure
• disrupt, confuse, attack cohesion and will Deploy friendly infrastructure
• communication, navigation, supplies, weapons
• High-quality low-cost real-time intelligence available to small tactical units
ISAT DARPA9
Symbiosis Between People and Robots
• The robot ecology needs to intermesh with the human organization in a symbiotic relationship
People are better at some things Robots are better at some things
• Robots will be the remote extension of people Robots must support people rather than force people to
support robots People are freed to make the higher level judgements
• in command without having to control
• The currencies of the self-sustaining robot ecology are energy and information
• they trade against each other and between themselves• they need to be supplied at the right places and times
ISAT DARPA10
Application Scenarios
• Remote exploration
• Tagging of people/trucks/ships/submarines
• Self-deploying communications/power network
• Search and rescue
• Battlefield surveillance, mine countermeasures
• Response to bio/chem attack
• Monitoring (infesting) a building
• Monitoring remote site for underground facilities (UGF)
• Support for military operations in urban terrain (MOUT)
ISAT DARPA11
UGF
• Threats: missile sites, weapons factories (e.g. biochem), command facilities, storage, weapons research
• What needs to be done: covertly characterize the facility (activity and structure) and possibly disrupt it
• Task List: monitor input/output of facility (roads, vents, effluent), sense nearby, sense inside, guide weapons, disrupt facility
• Steps: locate, infiltrate/disrupt, infestation, gather information; establish logistical chain for communication, sample retrieval and/or facility disruption
ISAT DARPA12
Underground Facility Characterization
UAV follows; releases microflyers, “seeds”
pods, creepers, burrs, mobile
(maybe satellite detect)
burrowing device from mother plant down to buried targets
communication relay to hill
creeper down air vent;burr placed inside;set up sensor net
(vibrations, gases, etc.)
[not to scale]
ISAT DARPA13
MOUT
• Threats: snipers, suicide bombers, biohazards, traps/mines; complication of neutrals as shields, chaos and confusion
• What needs to be done: avoid entering circle of lethality while establishing order and control
• Task List: navigation, communication, clearing, securing cleared areas, security in crowded/cluttered areas
• Steps: long-range deployment (e.g. to rooftops), local self-deployment, sense assess and reposition cycle, weapons use; diversity and numbers to overcome countermeasures
ISAT DARPA14
Military Operations in Urban Terrain
Camouflaged devices for tracking, scanning, extracting bio-samples
Robo-insects gain access inside doors/windows, around corners,
Sensors defend secured areas
Creeper/climbers gather indoor /outdoor info; form comm relay
not to scale
Microflyers “harvest” bio-samples
ISAT DARPA15
Why Can’t We Just Do This Today?
• There are some key systems challenges Scaling
• 10’s (now) to 100’s and 1000’s
Heterogeneity
• Symbiotic relationships of plantbots, mobots, and people
Adaptivity
• Context-aware self-organizing systems
• Some holes in base technology research areas Mobility Self-configuring networks Sensors Energy sources Cooperative behavior S
yst
em
iss
ues
sup
port
ed
by t
ech
nolo
gie
s
ISAT DARPA16
Systems Issues Relate to Technologies
Evaluation Scale: 0 = no idea 1 = fragile lab demo 2 = solid lab demo 3 = real stuff
Sca
ling
Hete
rog
eneou
s
Ad
ap
tabili
ty
Mobility
Self-configuring networksSensors
Energy sources
Cooperative behavior
NA 1 1
1 1 0
2 1 2
NA 1 0
1 0 1
Each of these systems issuescan only be pushed forwardwith adequate support fromthe underlying technologies.
The technologies havecertain levels of developmentas they relate to the systemsissues.
ISAT DARPA17
walking, climbing, reaching, standing, peering...Mobility: rolling, boring, swimming, creeping, hatching, flying,
ISAT DARPA18
Plantbots
• Current Examples: factory robots, sensor networks
• Future Examples: solar net, sensor net, sensor seed, creeper vine, balloon
launcher, burr, lure, tumbleweed, bio-station, any sci-fi alien plant form...
ISAT DARPA19
Plantbots
• Capabilities Accumulate/convert energy, information, provide shelter
(e.g., for short-lived bio-sensors), resupply; no self-locomotion for whole plant
• Benefits Limited mobility (seeds, creepers) can lead to advantage
in information or energy collection
Will provide the infrastructure for the mobile ecology components
• Challenge: requires extensive new research to devise appropriate forms and interoperation
ISAT DARPA20not to scale
air drop
spreads over tree
climbs down
sends out network
on ground mobile 'bots crawl
on jungle floor
climbs up,
establishes newnettwork
Communications Self-Deployment
ISAT DARPA21
Sensor State of the Art• Current:
Lots of low-power compact sensors exist
• acoustic, magnetic, seismic, pressure, IR, and visible
Other sensors require considerable development to meet reliability/size requirements, e.g. bio/chem
In general, cost dominated by communications and signal processing, rather than the sensor itself
• Imaging (IR or visible) costly in signal processing and (especially) communications
• Active sensors (e.g. radar) costly in power; require energy support network, cueing by other sensors for sustainability
• Future - Systems Approach: Exploit large numbers of sensors via self-organizing mobile
networks
ISAT DARPA22
Self Configuring Networks
• General-Purpose Networks won’t work: set-up is labor-intensive, even for military field command
posts
can’t be deployed in denied areas
pushing the limits result in high energy/complexity costs
• Future Mobile Sensor Networks by contrast are relaxed in all aspects if processing is done locally
exploitation of application and mobility allows energy-efficient and scalable design
ISAT DARPA23
Benefits of Mobile Sensor Networks
• Current: static distributed sensor net provides dense data gathering but, taxes information management through large numbers
• Small motion can dramatically improve detection and communication
e.g., maximize field of view, line-of-sight, form synthetic apertures
with better signal need many fewer elements
• Larger motion enables dynamic network deployment repair network failures, track and investigate threats beyond initial region of sensors extend or change detection region
ISAT DARPA24
Energy Generation/Extraction/Distribution
• Many methods 1. battery exchange 2. wires (incl. telephone and power grid) 3. solar 4. wind/water/waves 5. beaming (incl. concentrator mirrors) 6. hydrocarbon/fuel cells 7. convoys/depot system 8. animals (burrs and lures) 9. vehicles (burrs; exploit vibrations)10. hybrid, e.g., both capacitors and batteries for high currents
• Research required into how to best combine methods for particular systems and missions
ISAT DARPA25
Energy Conversion / Sustainment
plugs in
creeper comes out
micro-flyer moves battery
ISAT DARPA26
Future Energy Management
• Sustainment through ecology Design of energy system has large impact on
sustainability; e.g. plantbot energy network for energy accumulation and distribution
• Efficient use through distributed information Network provides global information to minimize
energy waste•navigation assistance, actuation/mobility avoidance,
resource discovery and management, exploitation of heterogeneity of ability/location
ISAT DARPA27
Cooperation: The Lessons of Ants
• Specialization and castes enable range of tasks to be performed
• Cooperative behaviors enlarge the set of tasks
• Main benefits of colonies however are: parallelism of tasks collective reliability with individual unreliability
• Ants apply distributed algorithms for collective control
• Much more research is needed to enable robot colonies to get these kinds of benefits
ISAT DARPA28
networking, competing, cooperating, distributing, sweeping...
Current cooperative robots are mostlyhomogeneous, and never more than20 robots
ISAT DARPA29
Robot Cooperation Challenges
• Centralized systems are brittle and require excessive communications resources.
Must identify effective heuristics for distributed coordination
• Communications and energy network self-organization cannot be general purpose
Cooperation must be pursued in applications context
• Lack of operational data Field tests to discover the needed behaviors for particular
missions, and integrate human operators and larger military/industrial infrastructure
• Lack of general theory of cooperation With a better understanding, can reduce number of
experiments
ISAT DARPA30
Robot Ecology Today
• Factory automation:
adjust environment for convenience of robots
• Global economy:
large infrastructure in place for symbiotic human/machine interaction on regional and global scales
• Battlefield:
unpredictable environment and no infrastructure, and thus many people to sustain each robot
• Need sustained autonomous operation in diverse environments
ISAT DARPA31
Robot Ecology Tomorrow
• Scaling More than 20 robots
• Heterogeneous robots Diverse sets of robots working together in
sustained missions
• Adaptivity Context-aware adaptation among members of
the ecology for operation in unplanned environments
ISAT DARPA32
Getting There
• Experiments
short-term, incremental progress
• integration of existing components, medium scaling
long-term, revolutionary steps
• incorporation of new algorithms, components, large scale
standard test conditions, and real-world
• Standard parts
modular robot software and hardware for plug and play
• enables creation of diverse, distributed research community
• Fundamental theoretical research
cooperation, scaling, adaptation