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Oussama Khatib

Researcher at Stanford University

Publications -  295
Citations -  34552

Oussama Khatib is an academic researcher from Stanford University. The author has contributed to research in topics: Robot & Robot control. The author has an hindex of 68, co-authored 288 publications receiving 31259 citations. Previous affiliations of Oussama Khatib include University of Tokyo & University of Notre Dame.

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Journal ArticleDOI

Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
BookDOI

Springer Handbook of Robotics

TL;DR: The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications.
Book

Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Journal ArticleDOI

A unified approach for motion and force control of robot manipulators: The operational space formulation

TL;DR: A framework for the analysis and control of manipulator systems with respect to the dynamic behavior of their end-effectors is developed, and the unified approach for motion and force control is developed.
Book ChapterDOI

Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: In this article, a real-time obstacle avoidance approach for manipulators and mobile robots based on the "artificial potential field" concept is presented, where collision avoidance, traditionally considered a high level planning problem, can be effectively distributed between different levels of control.