Dr. Oussama Khatib
The PhysOrg article Scientists study how to make humanoid robots more graceful said
Infants learn how to move by recognizing which movements and positions cause them physical discomfort and learning to avoid them. Computer science Professor Oussama Khatib and his research group at the Stanford Artificial Intelligence Laboratory are using the same principle to endow robots with the ability to perform multiple tasks simultaneously and smoothly.
“Humanoid robots today can walk and wave, but they cannot interact with the world,” Khatib said. “We are developing robots with the capability to physically touch, push and move objects.”
Khatib’s project is one aspect of the Honda Humanoid Robot Project, which aims to build human-friendly robots that can perform useful tasks in a complex, changing environment. Honda recruited Khatib to work on its project after he impressed company officials in 1995 with his twin robots Romeo and Juliet, mobile robot arms that can cooperate to perform complicated tasks, such as lifting a long length of pipe.
His inspiration for this new generation of robots came from humans themselves. In pondering the challenge of robotic movement, Khatib noticed that humans perform physical tasks in ways that minimize effort and discomfort. For example, while taking a sip from a hot cup of coffee, most people naturally hold their forearm at about a 45-degree angle, not up near their ear or down by their side. “They use the mechanical advantage of their bodies to perform the task while assuming postures that minimize muscular effort,” he said.
Oussama Khatib, Ph.D., FIEEE is President of
IFRR, the International Foundation of Robotics Research, and
Department of Computer Science,
His research is in autonomous robots, human-centered robotics,
human-friendly robot design, dynamic simulations, and haptic
interactions. His exploration in this research ranges from the
autonomous ability of a robot to cooperate with a human to the haptic
interaction of a user with an animated character, virtual prototype, or
He is a member of the
Manipulation Group, and
Stanford AI Laboratory research groups.
His active projects are Elastic Strip Framework, Haptics, Human Motion Synthesis, Human-Friendly Robot Design, Romeo & Juliet – Stanford Assistant Mobile Manipulations, SAI – Simulation & Active Interfaces, Soft Tissue Modeling – towards real time simulation, STAIR: The STanford AI Robot, and Teleoperation.
Oussama authored Real-Time Obstacle Avoidance for Manipulators and Mobile Robots and Inertial Properties in Robotic Manipulation: An Object-Level Framework, coauthored Experimental Robotics IX: The 9th International Symposium on Experimental Robotics (Springer Tracts in Advanced Robotics), Force Strategies for Cooperative Tasks in Multiple Mobile Manipulation Systems, The haptic display of complex graphical environments, and coedited Springer Handbook of Robotics. Read the full list of his publications!
Oussama earned his B.S. in Electrical Engineering at the Univ. de Montpellier, France in 1972, his M.S. in Electrical Engineering at the Univ. de Montpellier, France in 1974, his Advanced Diploma in Automatic Control at the l’Ecole Nationale Spuerieure de l’Aeronauque et de l’Escape, France in 1976, and his Ph.D. with his thesis of “Commande Dynamuqye dans l’Espace Ioerationnel des Robots Manipulateurs en Presence d’Obstacles” at l’Ecole Nationale Spuerieure de l’Aeronauque et de l’Escape, France in 1980. He was awarded a IEEE Fellowship in 2003 and the Japan Robot Association (JARA) Award in Research and Development in 1996.