Luminary Presentation 2013 PHM Conference, New Orleans, LA Autonomous Robotic Reconnaissance Missions in Extreme Space Environments Prof. Dr. Wolfgang Fink1,2 Associate Professor Edward & Maria Keonjian Endowed Chair AIMBE Fellow 1Depts. of Electrical & Computer Engineering, Biomedical Engineering, Systems & Industrial Engineering, Aerospace & Mechanical Engineering, and Ophthalmology & Vision Science Visual and Autonomous Exploration Systems Research Laboratory, University of Arizona, Tucson, AZ 2California Institute of Technology, Visual and Autonomous Exploration Systems Research Laboratory, Division of Physics, Mathematics and Astronomy, Mail Code 103-33, Pasadena, CA © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Thank you!!! Carl Byington Andrew Hess Tim Wilmering Karl Reichard Ginger Shao Jose Celaya Shankar Sankararaman Indranil Roychoudhury Yvonne Lopez Roxane Rose et al. © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Acknowledgements Collaborators: Mark A. Tarbell Visiting Scientist and Senior Research Scientist Visual and Autonomous Exploration Systems Research Laboratory Caltech/University of Arizona Wayne Waller Former Director Digital Media Center Caltech Colleagues at various Institutions Funding Support: DOD, DOE, NASA, NSF, Bausch & Lomb © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Motivation © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Planetary Bodies of High Interest [Images Courtesy NASA] © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona OSIRIS-REx: Asteroid Sample Return Mission 2016 © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Global Scale: Vast Canyon Systems such as Valles Marineris Image credit: T. Hare, USGS © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Global to Regional Scale: Central Valles Marineris Image credit: T. Hare, USGS © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Regional Scale: Melas Chasma Image credit: T. Hare, USGS © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Regional to Local Scale: Ophir Chasma Ophir Chasma terrain image courtesy ESA/DLR/FU Berlin (G. Neukum) © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Example of Recent/Transient Events: Dark Slope Streaks [Images courtesy of NASA/JPL/MSSS] © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Example of Recent/Transient Events: Light-toned Gully Deposit [Images courtesy of NASA/JPL/MSSS] © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Example of Recent/Transient Events: New Impact Crater (also: Volcanoes, Fires, Floods) [Images courtesy of NASA/JPL/MSSS] © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Tier-Scalable Reconnaissance & Autonomous Robotic (Space) Exploration © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Traditional Mission Architectures Mars Reconnaissance Orbiter (courtesy of NASA) Mars Science Laboratory Rover Mission (courtesy of NASA) Phoenix Lander Mission (courtesy of NASA) © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Tier-Scalable Reconnaissance: 4 Autonomous C ISR Architecture Fink et al., PSS 2005 © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Raytheon Future C4ISR Architecture (TSAT) © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Financial Disclosure: Existing Caltech Intellectual Property (IP) Patent number: US 6,990,406 Title: “MULTI-AGENT AUTONOMOUS SYSTEM” Authors: Wolfgang Fink et al. Patent number: US 7,734,063 Title: “MULTI-AGENT AUTONOMOUS SYSTEM” Authors: Wolfgang Fink et al. Patent number: US 7,742,845 Title: “MULTI-AGENT AUTONOMOUS SYSTEM AND METHOD” Authors: Wolfgang Fink et al. © Copyright 1998-2013 Visual and Autonomous Exploration Systems Research Laboratory at Caltech/University of Arizona Tier-Scalable Reconnaissance Paradigm and Robotic Test Bed Featured in SCIENCE 30 July 2010 Vol 329 NEWSFOCUS NEWSFOCUS Which rock? On Mars, the robot Opportunity Sensorweb, a group of half a dozen NASA ceed. He dreams of robots that can experi- solution (look at the fi nal digit) with no guid- needed some human help to spot this meteorite. satellites that monitor Earth’s atmosphere. ment with their own “neural networks”— ance. And by focusing on one bit, the com- Some scan large sections of Earth’s surface their internal architectures for taking inputs, puter freed 23 other bits for different tasks. Venus, for example, 450°C surface temper- and pick out a fl ood or a volcanic plume from processing information, and producing out- In other contexts, such self-confi guring net- atures and pressures comparable to those space. They beam the data to ground-based puts—and can, like humans, form their own works have helped scientists design circuits a kilometer deep in the ocean will destroy computers, which in turn direct higher- rules for exploring. and new drugs. the onboard computers of any lander within resolution satellites to focus on the event— McGuire says certain architectures have Ultimately, Fink says, he hopes to instill 5 hours, tops. To get anything done, the all without human input. Chien hopes to advantages in different applications. With a something like curiosity in robots. That kind lander will need to perform experiments, expand the work to other planets. But the so-called Hopfi eld neural network, for exam- of programming would go far beyond algo- such as sampling soil, without human input. instruments can spot only a short list of ple, a computer can recognize an entire pic- rithms his team has developed to help robots Rendezvous missions with comets or predefined events; they cannot find any- ture stored in memory after seeing only a frac- calculate the best angle to stretch out an arm asteroids and landings on distant moons thing interesting or new on their own. Asked tion. Many robots come equipped with mul- to grasp an object or scoop soil. “We’re after would also benefi t from more autonomous whether the system could shift its attention tiple lenses and cameras that take pictures on the intent to deploy the arm. How does the robots, researchers say. On Saturn’s moon on its own between the two most notable different scales, so the capability to tag small spacecraft know where it wants to dig? This Titan, radio waves carrying scientists’ geological events of the past few months, the snippets as familiar would help make the is of interest to me.” instructions take 90 minutes to arrive from Eyjafjallajökull volcano eruption in March robot more effi cient in selecting which scenes EXPLORATION Earth. Yet a probe flying through Titan’s and the BP oil slick in the Gulf of Mexico to shoot or not shoot. The fi rst test? atmosphere would have to negotiate hazards in April, Chien groans: “I wish, I wish.” Smart, curious robot explorers wouldn’t have in real time, notes Wolfgang Fink, a computer To solve problems of data filtering and to work alone. Fink envisions a multitier Making Smarter, Savvier Robots scientist working at the California Institute interpretation, some researchers are work- scheme of robots with satellites, blimps or of Technology and the University of Arizona. What machines of the future really need to learn, say experts who ing to cultivate a robot’s taste for the unusual. balloons, and platoons of ground rovers. An “If it’s about to fl y into a mountain range, it Sometimes scientists want to study the most intelligent satellite would direct the blimps plan to have them explore the far reaches of the solar system, is more can’t say, ‘I’m fl ying into a mountain range. representative feature around, but more often to canvass certain areas. The blimps, in turn, independent behavior Please advise,’ and wait 1½ hours.” on July 30, 2010 they are intrigued by anomalies. “If the whole would direct surface rovers to scout hydro- on July 30, 2010 Scientists also hope that greater intel- desert is smooth and one area is rough, that’s thermal vents or rappel down cliff faces with ligence will make robots more efficient, interesting,” says Chien. “If the whole desert a cable. Based on feedback between each tier, improving their “energy storage, memory, is rough and one area is smooth, that’s inter- the satellite would decide which sites to con- computational throughput, communication esting. If you really don’t know about the centrate on and how best to deploy the other downlink bandwidth, and heating and cooling environment, you have to fall back on some- machines. It would judge when to risk send- capability,” says Larry Matthies, a computer thing like outliers.” ing rovers into dangerous areas like active scientist