Towards a Robotic Ecology

1. Towards a Robotic Ecology Draft BriefingAugust, 1999 Rodney Brooks Greg Pottie (MIT) (UCLA)

2. 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 might 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.

3. 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 The Robot Ecologists GUEST PRESENTERS COMMITTEE ITINERANTS

4. Outline • Robot Ecology Vision • Support Technologies • Scenarios • Research Agenda

5. What Will Robot Ecology Do? • DARPA is investing in many UXVs for individual mission classes • There is no infrastructure for robot missions other than that supplied by people, meaning that either • people are put in harm’s way supporting robots • or, the class of robot missions is a priori very limited • Robot ecologies can • provide a rapid infrastructure deployment mechanism • enable robotic missions for tasks that people can’t or shouldn’t do • provide support for manned missions • reduce logistical support for sustained robotic missions

6. What Is A Robotic Ecology? • It is the extension beyond the idea of an ‘animal’-like robot to a collection of ‘animal’- and ‘plant’-like robots and support elements; collection as super-organism • It provides a self-constructing infrastructure that enables the collection to enhance their individual missions and prolong the total mission life • Teams of robots will self-organize and accomplish tasks collectively where no single part understands the whole; permits diverse tasks to be accomplished, graceful degradation

7. caterpillar (mobile sensor) “seed” sensors mother plant stationary sensor Battlefield Scenario

8. What Sorts Of Missions? • Surveillance and reconnaissance in areas that are high risk or denied • urban environments • hostage situations • chemical or biological threats • hidden or buried targets • Enables new capabilities • getting specialized sensors into the right places • long term observations • covert sensing in hazardous environments • tagging of targets

9. What Sort Of Infrastructure? • People infrastructure • energy, transportation, communication, water, food, health • Robot infrastructure • energy, communication, expendables, repair, reconfiguration • ecological architecture: what to repair vs. replace vs. do without (redundancy); continues to function at some useful level even absent some parts

10. Many Scenarios • Monitoring a remote site with suspected hidden facility • Remote exploration • Tagging of ships/submarines • Self-deploying communications/power network • Search and rescue • Battlefield surveillance incl. minefield replacement • Support for MOUT

11. Some Critical Ideas • Resupply of expendables (e.g., energy) • Self-configuration of heterogeneous distributed systems • Collaborative vs. individual behavior • Scavenging for resources that are lying around (e.g., electric power outlets, communication infrastructure) • Opportunistic ride hitching • Active motion to maintain concealment • Active motion to maximize intelligence gathered • Active motion to benefit communication trade-offs • Autonomy and self-configuration simplifies logistics

12. The Base Technologies • Actuation • Sensors • Communication • Power • Integration into ecology

13. The Brooks Scale:0= no idea1= fragile lab demo2= solid lab demo3 = real stuff Environments:U= airV= waterW= indoorX= road networkY = rural/outdoorsZ = urban • Fixed robots: • > 10 kg: 3 -- factories, hospitals, entertainment • Energy-scavenging robots: • 3U (solar flight > 10 kg), 0VWXYZ Robot Capability/Mobility • Mobile robot: • > 10 kg: 3UVWXYZ • 1-10 kg: 3UVW, 2X, 1YZ; • 100g-1kg: 3UV?,2WXYZ; • < 100g: 0 • BARRIERS: energy, navigation and control heuristics, scaling issues for small sizes

14. rolling, boring, swimming, creeping, hatching, walking, climbing, reaching, standing, peering...

15. Plantbots • Accumulate energy, information, provide shelter (e.g., for short-lived bio-sensors); no self-locomotion for whole plant • Current Examples: factory robots • Research Examples: solar net, sensor net, sensor seed, creeper vine, balloon launcher, burr, lure, tumbleweed, bio-station, any sci-fi alien plant form... • Slow accumulation or conversion of energy to resupply mobots, or other plantbots in connected network • Limited mobility (seeds, creepers, air ducts) can lead to advantage in information or energy collection • Infrastructure for the mobile ecology components

16. Sensor State of the Art • Compact acoustic, magnetic, seismic, pressure, IR, and visible sensors have been tested with low power requirements • Imaging (IR or visible) costly in signal processing, but still dominated by communication of image • Bio/chem sensors appear to require considerable further development to meet reliability/size requirements • Active sensors (e.g. radar) costly in power • Cost of IC-based sensors dominated by communications and signal processing, rather than the sensor itself • Better sensor collaboration schemes can consequently have large impact

17. Ad Hoc Networks • Most network set-up is labor-intensive, even for military field command posts; completely unacceptable for low-cost robotics • Extensive work in packet radio networks over 20 years; end-to- end connectivity in high mobility causes low efficiency • If push to bandwidth/latency/dynamics limits, very difficult design • Sensor networks are relaxed in all aspects if processing is done locally; allows energy-efficient and scalable design • Low mobility robots may similarly be feasible, at progressively higher energy cost with mobility.

18. 1 0 0 1 2 2 3 3 4 4 5 5 8 8 7 7 6 6 9 9 11 11 10 10 13 13 12 12 14 14 16 16 17 15 17 15 0 1 0 1 2 2 3 3 5 5 4 4 8 8 7 7 6 6 9 9 11 11 10 10 12 13 12 13 14 14 16 16 17 15 17 15 Network Self-Organization An 18-node random topology • Link formation as time progresses • Note the formation of subnets with dif- ferent colors

19. Networking/Mobility Trades • Example of many sensors in an area • Cooperation/collaboration results in limited mobility needed for each node (small area to search, improved SNR) • Small motion may result in improved detection/communi-cation, resulting in needing many fewer elements • Larger motion may enable repair of network failures, investigation of threats beyond initial region of sensors; multihopped network allows larger extension • Heterogeneity of communication and mobility capabilities can lead to richer set of behaviors

20.  air drop  spreads over tree  climbs up,establishes newnettwork  climbs down   mobile 'bots crawlon jungle floor sends out networkon ground Communications Self-Deployment not to scale

21. 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

22. Energy Storage Media • Capacitors: 18 J/g • Mechanical: springs = 1/2 kx2 • Potential energy: mgh (balloons, water pumping/osmosis) • Batteries: 600 J/g; 900 J/g likely in future • Micro-gas turbines: est. 6000 J/g (experimental) • Sugar: 17,000 J/g • Fat: 39,000 J/g (1 ''calorie'' = 4186 J)

23. 1kg lifted @ 1% efficiency • 1000 dig 1minto rock  1kg lifted @ 100% glide 1kg on 100:1 ratio • • 100 • • • 10 r2 loss • • • 1kJ r4 loss • • • 100 increased infrastructure per bit • • r4 loss 10 Energy (Joules) Iridium2.4kb  • •  1 cellular30kb fiber1Gb cordless80kb • ~   100 signal processingfor identification •  10 RFM10kb 0.2 dB/km (use repeaters) 1mJ detect heavy vehicle (seismic) 0.1mJ 0.1 1 10 100 1km 100km Distance Some Energy Trades

24. Energy/Information Trades • Design of energy system has large impact on sustainability; e.g. plantbot energy network for energy accumulation and distribution • Information system also has large impact on energy efficiency: navigation assistance, actuation/mobility avoidance, resource discovery and management, exploitation of heterogeneity of ability/location

25. • • Task Duration • • • • constant energy • • • Energy Intensity When to Resupply? energy resupply required batteries possible constant energy

26.  micro-flyer moves battery  plugs in  creeper comes out Energy Conversion / Sustainment

27. Deploy by Land, Sea, or Air? • Macro systems: bulk transportation uses least energy by water, next by land, and then by air; but land transportation has had enormous infrastructure investment to enable use of wheels • Micro systems: unless use opportunistic transport, expect energy efficiencies highest for water and air, least for land. • Water and land provide opportunities to generate surplus energy; air systems are net consumers, but can be involved in resupply

28. Robot Ecology Today • Factory automation: adjust environment for convenience of robots • Battlefield: many people to sustain each robot, little coordination across platforms • The industrial infrastructure: symbiotic human/machine interaction on regional and global scales • Would like to achieve sustained autonomous operation, with the ecology in the role of the environmental modification or infrastructure.

29. Robot Ecology Trade-offs • Robot capability/mobility • Collaborative behavior • Communications/networking • Energy efficient/constrained interactions/scenarios • Energy conversion/sustainment • Can do trades among these things, as well as looking into new techniques which could make each of them more efficient. • It is the interplay that is most important.

30. size scaling Task Duration specialization cooperation 0.1ms 1ms 10 100 1 10 100 1kb 10 100 Energy Intensity Collaborative Behavior

31. 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 see whether robot colonies will get these kinds of benefits

32. Ecce Bio-Robo-Eco? • Can selectively breed characteristics over many sigma -- many potentially useful features, with reproduction • Harvard Rule of Animal Behavior: under the most carefully controlled laboratory conditions, the animal will do... • Better to reverse engineer the mechanism, after it has been bred. • RNA selection over multiple steps can increase sensitivity to particular species by many orders of magnitude -- then use to detect particular agents with high selectivity. • Evolution is unpredictable: controllability strong motivation for purely artificial ecologies; ethical issues, unintended consequences.

33. networking, competing, cooperating, distributing, sweeping...

34. Robot Collaboration Challenges • Identification of effective heuristics for distributed coordination-- centralized systems are brittle, require excessive communications resources. • Communications and energy network self-organization; cannot be pursued in isolation from application. • Lack of operational data; what behaviors are actually needed for particular missions • Integration with larger military/industrial infrastructure, suitable human interfaces • Plantbot/mobot coordination; in general, theory for management of highly heterogeneous and numerous elements

35. Underground Facility Inspection (maybe satellite detect)   UAV follows; releases microflyers, “seeds” pods, creepers, burrs, mobile  communication relay to hill   creeper down air vent;burr placed inside;set up sensor net(vibrations, gases, etc.) burrowing device from mother plant down to buried targets [not to scale]

36.  Mobile/stationery (floating/immersed)sensors provide supplemental infoto FRIENDLY submarines  Sensors launched  Mobile/stationery sensorsidentify, attach to and/or monitorENEMY submarines, relay info Submarine Reconnaissance not to scale

37. Sensors locate victim trapped in inaccessible danger zone  summoned by signal from victim/other sensors,or programmed to approach after scanning Micro-robots (air-borne and/or amphibious) provide immediate triage if necessary  H20 rations Larger robots transport emergency supplies, provide first aid(treatment and supplies)  Search & Rescue already in place prior to disaster,programmed to scan and signal for help stationery sensors roving sensors not to scale

38. Military Operations in Urban Terrain Sensors defend secured areas Microflyers “harvest” bio-samples Camouflaged devices for tracking, scanning, extracting bio-samples Creeper/climbers gather indoor /outdoor info; form com relay Robo-insects gain access inside doors/windows, around corners, not to scale

39. Moving Forward • Communications • Science of collective behavior • Robotic software and hardware standards • Robotic ecology • Experiment set

40. Robo Web • Creation of self-organizing communications, signal processing/data storage networks for robotic ecology applications, including personnel support • Can exploit: heterogeneity of resources, actuators/sensors for alternative communication modes, physical transport of data, motion of relays and antennas • Research issues: exploration of this expanded design space, reliable distributed algorithms, communication network self-repair, difficult environments

41. Cooperation • Premise: collection of heterogeneous cooperating robotic elements will perform missions more robustly or economically by becoming the infrastructure • Critical Issues: how do individuals identify what is important to the collective and communicate just that; what principles would turn collective behavior, self-organization, and adaptation into a real science of general application; attention mechanisms; survival principles; interplay of information and energy exchange

42. Standards • Most robot design is an exercise in vertical integration, and little compatibility across platforms • Design interfaces at several hardware and software levels: permits building block construction of ecology, allows researchers to focus on different levels (cooperation vs. actuation) • Aim for “Lego Mindscape” for researchers; same building blocks can be used for wide variety of systems--lower cost, innovative development; plug and PLAY.

43. Ecology Building Blocks • New modes of locomotion for both mobots and plantbots • Standard power and communication connectors; docking mechanisms; energy systems • Robots in several ranks of sizes, but particularly very small ones • Robotic plants of many types • Burrs and lures for opportunistic transport and tagging • Protocols (centralized vs. distributed)

44. Experiment Set • Make self-organization real with existing (but possibly tweaked) DARPA projects; six month schedule between successive demos • Example: long-range navigation, such that no single robot can do it without resupply or cooperation; sequence of tests of increasing difficulty • Revolutionary scenarios: requires new hardware, demos may take place near end of program, but with early involvement of end users • Standardized test sets and environments

45. Ah Ha! • An ecology of cooperating and diverse robots (plantbots and mobots) offers potential for robust, sustainable operation at low cost • Long range potential to revolutionize military operations: many robots per warfighter, new missions, fundamental change in missions