Adam Coates, talk, gold medal for autonomous helicopter
Author:
Coates, Adam
Author (no Collectors):
Coates, Adam
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Adam Coates for acrobatic flight maneuvers of the Stanford autonomous helicopter. Autonomous helicopter flight is widely regarded to be a highly challenging control problem. It is particularly difficult to design controllers for non-stationary maneuvers in which the helicopter goes through various flight regimes, extensively exposing the great complexity of helicopter dynamics. Despite these challenges, human experts can reliably fly helicopters through a wide range of maneuvers, including aerobatic maneuvers at the edge of the helicopter's capabilities.
Pieter Abbeel and Adam Coates developed apprenticeship learning algorithms that leverage expert demonstrations to efficiently learn good controllers for the tasks being demonstrated by an expert. These apprenticeship learning algorithms have enabled their helicopters to significantly extend the state of the art in autonomous helicopter flight and aerobatics. Their experimental results included the first autonomous execution of a wide range of maneuvers, including flips, rolls, loops, auto-rotation landings, chaos and tictocs, which only exceptional human pilots can perform. Their results also included complete air shows, which required autonomous transitions between many of these maneuvers. Their system performs as well, and often even better, than an expert human pilot.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Bruce Baumgart, talk, gold medal for creating the SAILDART archive
Author:
Baumgart, Bruce
Author (no Collectors):
Baumgart, Bruce
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Bruce Baumgart for creating the SAILDART computer archive. Preserving digital records and making them accessible for the long term is a difficult task both because digital recordings, especially those on magnetic media, don't last long and because write/read technologies keep changing as do file formats. Bruce Baumgart, with help from Martin Frost and others, has been able to preserve most of the records of the Stanford Artificial Intelligence Lab from the 1970s and '80s and has made the public files from that period publicly accessible on http://www.saildart.com . Private files are accessible there to their owners via logins. He did this with a great deal of personal effort and at his own expense. The problem of preserving such records for the very long term, as we believe they should be, is not yet solved but this effort constitutes a big step in the right direction.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Dan Klein, talk, gold medal for unsupervised probabilistic language parsing
Author:
Klein, Dan
Author (no Collectors):
Klein, Dan
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Dan Klein for revolutionary contributions to unsupervised probabilistic language parsing. Dan Klein wins this award for his pioneering contributions to the unsupervised learning of natural language structure. Klein's thesis work demonstrated the first computer system capable of acquiring high-quality grammars from raw text alone, answering a long-standing open question about the empiricallearnability of human languages. Along with his group at UC Berkeley, he has since continued to advance the state of the art in natural language processing using unsupervised and latent-variable methods. In addition to constructing fast and accurate syntactic analysis systems, his recent research has successfully tackled a variety of other language tasks. In the area of machine translation, for example, his work OIL syntactic correspondence has produced the best systems for learning latent translation alignments. In the area of reference resolution, his research has led to a fully unsupervised system that outperforms its supervised competitors. Recent results on historical reconstruction have demonstrated the most accurate system for the automatic inference of ancestral words from modern forms. Klein is the recipient of multiple academic honors, most recently including the ACM Grace Murray Hopper award, a Microsoft New Faculty Fellowship, a Sloan Fellowship, and multiple best paper awards.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Dan Swinehart, talk, gold medal for SAIL programming language
Author:
Swinehart, Dan
Author (no Collectors):
Swinehart, Dan
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Dan Swinehart for contributions to the SAIL programming language. The SAIL programming language and system was developed in the late 1960's by Bob Sproull and Dan Swinehart, with later contributions by Jim Low, Hanan Samet, Russ Taylor, Kurt van Lehn and others too numerous to mention. Derived from a class project, called Gogol, the language began with something resembling Algol-60 and then layered on contributions from many emerging language trends, including associative processing (based on Feldman's LEAP), records (typed compound data structures), references (typed pointers to same), support for multiple threads, and variable-length strings with automatic storage management, the latter inspired by a Bill McKeeman PUI-like project on campus. The system was coded entirely in Phil Petit's FAIL assembly language to support hard-core systems applications for which LISP and other available languages were arguably inappropriate. Among others, notable well-known applications developed in SAIL include Larry Tesler's PUB and early versions of Don Knuth's even more ambitious TEX document composition systems.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
David Stavens, talk, gold medal for DARPA Grand Challenge vision algorithms
Author:
Stavens, David
Author (no Collectors):
Stavens, David
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Honored for computer algorithms that led to the DARPA Grand Challenge victory. For his groundbreaking contributions to the winning DARPA Grand Challenge vehicle, and in particular his algorithms for adaptive speed control. His adaptive speed control algOlithm selected the best speed autonomously with machine learning, considering features such as road roughness, slope, and width. The algorithm could be trained to closely match a human driver's speed choices. This allowed Stanford to avoid massive human-tweaking of the race route, known as "pre-planning," that characterized some other teams. The algorithm includes a band-pass filter, designed by Gabe Hoffmann, to isolate the vehicle's suspension. David made contributions to several other aspects of the robot, including the watchdog program for software health monitoring and the adaptive vision system. In addition, David was on the launch team responsible for the vehicle on the morning of the race and, as TA for the Grand Challenge class, oversaw the very first end-to-end development of Stanley. He was also the principal safety driver for in-the-desert road tests. His other responsibilities included team coordination and media and investor relations. Using data from the event, David later published a self-taught learning algorithm that used haptic feedback from the IMU to enhance the laser perception beyond race performance.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Hendrik Dahlkamp, talk, gold medal for DARPA Grand Challenge "self-supervised learning"
Author:
Dahlkamp, Hendrik
Author (no Collectors):
Dahlkamp, Hendrik
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
For computer vision that led to the DARPA Grand Challenge victory. For his contributions to Stanford's autonomous vehicle Stanley, and specifically its computer vision system for long-range road detection. Called Stanford's "secret weapon" by a PBS documentary on the DARPA Grand Challenge, this system enabled Stanley to perceive and classify desert terrain in the distance as drivable or undrivable, and determine a safe traversal speed. The algorithm was a crucial contribution in two ways: First, it allowed Stanley to extend its sensing range from a classical laser-based perception range of 20 meters to a camera-based range of 40 meters, which led to a 40% increase in top speed and a win in the race. Second, it advanced a new paradigm in ru1ificial intelligence called "self-supervised learning", where the output of one sensor modality, the laser range finder, is used to generate online training data for a second sensor modality, the camera. This allowed Stanley to constantly adjust its road model to the environment, taking time-of-day, surface material, texture, shadows etc into account. Together with Intel Computer Vision Researcher Adrian Kaehler, Hendrik implemented a perception system that was able to react even to obstacles such as tank traps that it had never encountered before.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
John Chowning, talk, gold medal for computer music systems
Author:
Chowning, John M.
Author (no Collectors):
Chowning, John M.
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
John Chowning for creating the computer music synthesis system John Chowning initiated the computer music project at SAIL, with the indispensable help of undergrad student David Poole, that became the internationally recognized Center for Computer Research in Music and Acoustics (CCRMA). Along the way he discovered a frequency modulation scheme that could closely emulated the sounds of known musical instruments and many that are unknown. Software was not patentable at that time so he recruited grad student Andy Moorer to translate it into a hardware design that was patented through Stanford and licensed to Yamaha, which eventually incorporated it into a wide range of digital synthesis devices, from organs to cell phones, including the most widely sold synthesizer ever, the DX 7. The proceeds from that licensing agreement helped CCRMA get through a critical phase of its development-including the acquisition of the Foonly F2, built by David Poole-and eventually endow the ongoing programs at CCRMA.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Ken Salisbury for the design and build-up of the Salisbury robotic hand. Ken Salisbury designed the "Salisbury Hand" (originally known as the Stanford/JPL hand) while he was a graduate student at Stanford as an advisee of Prof. Bernie Roth in Mechanical Engineering. In collaboration with Carl Ruoff at NASA/Jet Propulsion Labs and Prof. Roth, the hand was designed to be a platform for investigation of robotic grasping and dexterous manipulation. Commercialized through Ken's "Salisbury Robotics" company in the early 80's this hand became a popular research platform for many years and continues to be an icon symbolic of robotic dexterity. In the years since, Ken's labs have spawned an number of well-known robotic and haptic devices, including the MIT-W AM arm (now known as the Barrett Arm from Barrett Technology), the PHANToM Haptic Interface from Sensable Technology, telesurgical devices commercialized by Intuitive Surgical, and most recently the first version of the Personal Robot that is now being commercialized by Willow Garage.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Larry Tesler, talk, gold medal for PUB document compiler
Author:
Tesler, Larry
Author (no Collectors):
Tesler, Larry
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Larry Tesler for creating the PUB document compiler. In 1971, Les Earnest recruited Larry Tesler to create a document compiler that would go well beyond RUNOFF by supporting advanced publishing features. The software Larry built during the ensuing six months featured automatic numbering, headings, multiple columns, figures, footnotes, front and back matter generation, and cross-references. Its power was unprecedented. It also was evidently the first document compiler that provided for embedded spreadsheets. Today, we would call it a "scriptable markup language". The scripting language was a subset of SAIL. In that pre-SGML era, the markup syntax was non-uniform but it did allow arbitrary text to be bracketed by tags.
Because it was written in SAIL and because its syntax required use of the entire SAIL character set, the audience for PUB was limited. Nevertheless, at ARPANET-connected universities with PDP-lOs, many a thesis was formatted using PUB. Because the code was open-source, Russ Taylor added FR-80 microfilm output and Rich Johnsson of Carnegie Mellon University (CMU) added font capabilities.
As with other markup languages, the output was often difficult to predict. At least two PUB users reacted to these shortcomings by developing better languages. Brian Reid, then at CMU, developed Scribe for nontechnical users. He implemented the first version entirely in PUB. Don Knuth developed TeX for authors of mathematical texts. Meanwhile, SGML and C took over as the basis for most future markup and scripting languages, and PUB became a forgotten milestone in digital publishing history.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Les Earnest, talk, gold medal for FINGER, an early social networking program
Author:
Earnest, Lester
Author (no Collectors):
Earnest, Lester
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Les Earnest for helping to start ARPAnet and creating the social networking program FINGER. During 1967-68 Les Earnest was a member of the ten person startup committee for the first packet switching network, which came to be called ARPAnet and later turned into the Internet. Their initial performance specifications were not too foresighted in that only two functions were specified: file transfer and remote computing, which came to be called Telnet. However the file transfer capability was adequate to support email when it came into use a short time later and the tight round trip communication requirement needed for Telnet made possible the much later interactive web services.
In the 1970s Les created the FINGER program, which could show who was currently logged in and, if not, when they last logged out. This was to help keep track of SAIL people who worked at all hours of the day and night. Given that nearly all SAIL software was made publicly accessible, a number of other laboratories with similar computer systems took copies of FINGER for their own use and soon requested that a network versioij be developed that could check on people at other sites, which Mark Crispin developed. FINGER also allowed each person to create a Plan file, tied to their email address, to describe such things as their planned work schedule or vacation plans. However in short order FINGER became a de facto social networking system, given that it facilitated finding which of one's friends were online and allowed people to post what amounted to personal blogs some 30 years before the term "blog" came into use. For more see http://asia.cnet.com/reviews/pcperipherals/0,39051168,61998604,00.htm . A Unix version was created by a UC Berkeley group that unfortunately had a security loophole that was exploited by the first Internet Worm, resulting in FINGER being suppressed on security grounds. Google is now developing a modem version called WEBFINGER.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Lynn Quam, talk, gold medal for Mars image processing
Author:
Quam, Lynn Herman
Author (no Collectors):
Quam, Lynn Herman
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Lynn Quam for creating an image retrieval system for planetary exploration. Lynn Quam and his colleagues developed an image indexing scheme for planetary exploration and picture differencing techniques to facilitate identification of things that changed over time. This was used by Carl Sagan and other astronomers who visited SAIL every few weeks to evaluate satellite photographs of Mars. Quam successfully solved the problem of detecting small changes in the planet surface in the presence of several extraneous factors. His system was subsequently applied to pictures of Mars taken by the Mariner 9 spacecraft while the mission was in progress.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Martin Frost, talk, gold medal for first computer network news service
Author:
Frost, Martin
Author (no Collectors):
Frost, Martin
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Martin Frost for creating the first network news service. Martin Frost, with input from John McCarthy and Les Earnest, created two successive news services that each was the first of its kind. Beginning in 1972, APE could be used either to connect to the Associated Press newswire or to search recent stories based on combinations of pre-selected keywords. Beginning in 1974 NS (for News Service) indexed and stored stories from both the Associated Press and New York Times news wires and allowed users to either search for recent stories using any combination or words or leave a standing request to be notified whenever a story appears that contains the specified words. NS was widely used by people on ARPAnet for general news information.
During the Three Mile Island nuclear incident in 1979 the emergency response team at Lawrence Livermore Lab found that they needed up-to-the-minute information on developments at the site but couldn't get it until they were provided with access to NS. During the Tiananmen Square protests in 1989, Chinese students in the U.S. wanted to pass information to friends in China but there were no Internet connections there then. NS was then set up to locate news about China and forward it to a student distribution list so that they could print the stories and fax them home. Commercial news services were developed later that now provide similar functionality to anyone who wants it and is willing to pay a subscription fee.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives
Mike Montemerlo, talk, gold medal for DARPA Grand Challenge technical leadership
Author:
Montemerlo, Mike
Author (no Collectors):
Montemerlo, Mike
Corporate Author:
Stanford Artificial Intelligence Laboratory
Description:
Mike Montemerlo was recognized for leadership and technical contributions that led to the DARPA Grand Challenge victory. Michael Montemerlo is being recognized for his leadership in Stanford Autonomous Driving Team, which led to the victory in the DARPA Grand Challenge. Mike was the chief software architect of the system, and his work influenced all aspects of Stanley's software, from hardware interfaces, perception, mapping, path planning, and control. Mike was the technical leader for the entire team, and his vision and technical strength guided all other team members in this successful project. The DARPA Grand Challenge was widely considered a milestone event for robotics. For the first time, robotic cars proved their ability to navigate extensive desert trails completely autonomously.
Topic:
Artificial intelligence
Subject:
Stanford Artificial Intelligence Laboratory
Language:
English
Physical Description:
1 video file
Publication Info:
cau and Stanford (Calif.)
Date:
November 22, 2009
Place created:
Stanford (Calif.)
Imprint:
Stanford (Calif.), November 22, 2009
Genre:
lectures
Repository:
Stanford University. Libraries. Department of Special Collections and University Archives