Jean-Claude Latombe | |
---|---|
Born | Pernes-les-Fontaines, France | May 16, 1947
Nationality | French American |
Alma mater | University of Grenoble National Polytechnic Institute of Grenoble |
Scientific career | |
Institutions | Stanford University National Polytechnic Institute of Grenoble |
Notable students | Suresh Venkatasubramanian Lydia E. Kavraki James J. Kuffner Jr. |
Jean-Claude Latombe (born May 14, 1947) is a French-American roboticist and the Kumagai Professor Emeritus in the School of Engineering at Stanford University. Latombe is a researcher in robot motion planning, and has authored one of the most highly cited books in the field. [1]
Latombe received his dual-Engineering Degree in electrical engineering and computer science from the National Polytechnic Institute of Grenoble (now Grenoble Institute of Technology) in 1969 and 1970, respectively, and a M.S. in electrical engineering in 1972, with the thesis Design of a Computer-Aided Instruction System in Electrical Engineering. In 1977, Latombe received a Ph.D. in computer science from the University of Grenoble with a thesis Artificial Intelligence for Design Automation.
He joined the faculty of INPG in 1980, and left in 1984 to join the Industry and Technology for Machine Intelligence (ITMI), a company he co-founded in 1982. In 1987, Latombe joined Stanford University as an Associate Professor, and has since been Professor (1992), Chairman (1997–2000), and Kumagai Professor (2001–Present) in the Department of Computer Science.
Latombe is an important figure in robotic motion planning. After Mark Overmars published the Probabilistic Roadmap Method (PRM) in 1992, Latombe and Lydia Kavraki independently developed the algorithm in 1994, and their joint paper with Overmars, Probabilistic roadmaps for path planning in high-dimensional configuration spaces, [2] is considered one of the most influential studies in motion planning, and has been widely cited (more than 1000 times as of 2008). More recently, Latombe has applied his knowledge in robotics to structural biology problems, and developed the PRM-based Stochastic Roadmap Simulation (SRS) to efficiently generate and analyze large collections of protein trajectories. [3]
In statistics, Markov chain Monte Carlo (MCMC) methods comprise a class of algorithms for sampling from a probability distribution. By constructing a Markov chain that has the desired distribution as its equilibrium distribution, one can obtain a sample of the desired distribution by recording states from the chain. The more steps that are included, the more closely the distribution of the sample matches the actual desired distribution. Various algorithms exist for constructing chains, including the Metropolis–Hastings algorithm.
Mechatronics engineering also called mechatronics, is an interdisciplinary branch of engineering that focuses on the integration of mechanical, electrical and electronic engineering systems, and also includes a combination of robotics, electronics, computer science, telecommunications, systems, control, and product engineering.
Computer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics, astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.
Markus Hendrik Overmars is a Dutch computer scientist and teacher of game programming known for his game development application GameMaker. GameMaker lets people create computer games using a drag-and-drop interface. He is the former head of the Center for Geometry, Imaging, and Virtual Environments at Utrecht University, in the Netherlands. This research center concentrates on computational geometry and its application in areas like computer graphics, robotics, geographic information systems, imaging, multimedia, virtual environments, and games.
Motion planning, also path planning is a computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games.
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots. Robotics is related to the sciences of electronics, engineering, mechanics, and software. The word "robot" was introduced to the public by Czech writer Karel Čapek in his play R.U.R., published in 1920. The term "robotics" was coined by Isaac Asimov in his 1941 science fiction short-story "Liar!"
Wolfram Burgard is a German roboticist. He is a full professor at the Albert-Ludwigs-Universität Freiburg where he heads the Laboratory for Autonomous Intelligent Systems. He is known for his substantial contributions to the simultaneous localization and mapping (SLAM) problem as well as diverse other contributions to robotics.
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree. The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem. RRTs were developed by Steven M. LaValle and James J. Kuffner Jr. They easily handle problems with obstacles and differential constraints and have been widely used in autonomous robotic motion planning.
The probabilistic roadmap planner is a motion planning algorithm in robotics, which solves the problem of determining a path between a starting configuration of the robot and a goal configuration while avoiding collisions.
Seth A. Hutchinson is an American electrical and computer engineer. He is the Executive Director of the Institute for Robotics and Intelligent Machines at the Georgia Institute of Technology, where he is also Professor and KUKA Chair for Robotics in the School of Interactive Computing. His research in robotics spans the areas of planning, sensing, and control. He has published widely on these topics, and is coauthor of the books "Robot Modeling and Control," published by Wiley, Principles of Robot Motion - Theory, Algorithms, and Implementations, with Howie Choset, Kevin M. Lynch, George Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian Thrun.
Steven M. LaValle is an American computer scientist, and a professor in the Faculty of Information Technology and Electrical Engineering at the University of Oulu. He was also an early founder and head scientist of Oculus VR until it was acquired by Facebook in 2014. He is best known for his work on RRTs, the Oculus Rift, and his book, Planning Algorithms, one of the most highly cited texts in the field.
In robotics and motion planning, a velocity obstacle, commonly abbreviated VO, is the set of all velocities of a robot that will result in a collision with another robot at some moment in time, assuming that the other robot maintains its current velocity. If the robot chooses a velocity inside the velocity obstacle then the two robots will eventually collide, if it chooses a velocity outside the velocity obstacle, such a collision is guaranteed not to occur.
Ant robotics is a special case of swarm robotics. Swarm robots are simple robots with limited sensing and computational capabilities. This makes it feasible to deploy teams of swarm robots and take advantage of the resulting fault tolerance and parallelism. Swarm robots cannot use conventional planning methods due to their limited sensing and computational capabilities. Thus, their behavior is often driven by local interactions. Ant robots are swarm robots that can communicate via markings, similar to ants that lay and follow pheromone trails. Some ant robots use long-lasting trails. Others use short-lasting trails including heat and alcohol. Others even use virtual trails.
For robot control, Stochastic roadmap simulation is inspired by probabilistic roadmap methods (PRM) developed for robot motion planning.
Lydia E. Kavraki is a Greek-American computer scientist, the Noah Harding Professor of Computer Science, a professor of bioengineering, electrical and computer engineering, and mechanical engineering at Rice University. She is also the director of the Ken Kennedy Institute at Rice University. She is known for her work on robotics/AI and bioinformatics/computational biology and in particular for the probabilistic roadmap method for robot motion planning and biomolecular configuration analysis.
OMPL is a software package for computing motion plans using sampling-based algorithms. The content of the library is limited to motion planning algorithms, which means there is no environment specification, no collision detection or visualization. This is intentional as the library is designed to be easily integrated into systems that already provide the additional needed components. For example, OMPL is integrated with ROS and MoveIt!. In 2012 OMPL won the Grand Prize at the Open Source Software World Challenge.
Oussama Khatib is a roboticist and a professor of computer science at Stanford University, and a Fellow of the IEEE. He is credited with seminal work in areas ranging from robot motion planning and control, human-friendly robot design, to haptic interaction and human motion synthesis. His work's emphasis has been to develop theories, algorithms, and technologies, that control robot systems by using models of their physical dynamics. These dynamic models are used to derive optimal controllers for complex robots that interact with the environment in real-time.
Nancy Marie Amato is an American computer scientist noted for her research on the algorithmic foundations of motion planning, computational biology, computational geometry and parallel computing. Amato is the Abel Bliss Professor of Engineering and Head of the Department of Computer Science at the University of Illinois at Urbana-Champaign. Amato is noted for her leadership in broadening participation in computing, and is currently a member of the steering committee of CRA-WP, of which she has been a member of the board since 2000.
Real-Time Path Planning is a term used in robotics that consists of motion planning methods that can adapt to real time changes in the environment. This includes everything from primitive algorithms that stop a robot when it approaches an obstacle to more complex algorithms that continuously takes in information from the surroundings and creates a plan to avoid obstacles.
Jean-Paul Laumond was a French robotician, research director at the CNRS, member of the French Academy of Sciences and the French Academy of Technologies.