- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
Search Results
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- Gold medals, Stanford Artificial Intelligence Laboratory Reunion
- Corporate Author:
- Stanford Artificial Intelligence Laboratory
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- Gold medals, Stanford Artificial Intelligence Laboratory Reunion
- Corporate Author:
- Stanford Artificial Intelligence Laboratory
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- John McCarthy, reminisces on the founding of SAIL and comments on three of the medalist talks
- Author:
- McCarthy, John, 1927-2011
- Author (no Collectors):
- McCarthy, John, 1927-2011
- Corporate Author:
- Stanford Artificial Intelligence Laboratory
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- Ken Salisbury, talk, gold medal for robotic hand
- Author:
- Salisbury, Ken
- Author (no Collectors):
- Salisbury, Ken
- Corporate Author:
- Stanford Artificial Intelligence Laboratory
- Description:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041
- Title:
- 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
- Collection:
- Stanford Artificial Intelligence Laboratory records, 1963-2009
- Manuscript number:
- SC1041