Advisory Board

Professor James J. Kuffner Jr.

James J. Kuffner, Jr., Ph.D. born in 1971 is an American roboticist and the CEO of Toyota Research Institute for Advanced Development (TRI-AD) and is perhaps best known as coinventor of the Rapidly-exploring Random Tree (RRT) algorithm, which has become a key standard benchmark for robot motion planning. James continues to serve as an Adjunct Associate Professor at the Robotics Institute, School of Computer Science, Carnegie Mellon University.

The "RRT-Connect" algorithm was developed as part of his Ph.D. research. This algorithm has become a key standard benchmark for sampling-based exploration of high-dimensional search spaces for robot motion planning. From 1999 until 2001, James was a Japan Society for the Promotion of Science (JSPS) Postdoctoral Research Fellow at the University of Tokyo, developing software and planning algorithms for humanoid robots. He joined the faculty at Carnegie Mellon University's Robotics Institute in 2002.

In Jan 2016, James joined the Toyota Research Institute (TRI) where he was appointed the Chief Technology Officer and Area Lead, Cloud Intelligence.

In March 2018, Toyota announced a $2.8 billion investment in the creation of a new company, Toyota Research Institute — Advanced Development (TRI-AD), with James as chief executive officer (CEO). TRI-AD is headquartered in Tokyo, and is reported to ultimately employ over 1,000 engineers for the development of software for automated driving and artificial intelligence.

James joined Google in 2009 and was a member of the software engineering team that developed the Google self-driving car. James is also known for introducing the term "Cloud Robotics" in 2010 to describe how network-connected robots could take advantage of distributed computation and data stored in the cloud.

James cofounded, with Andy Rubin, Google's investments in Robotics technology, built primarily from the acquisition of innovative companies such as Boston Dynamics, Schaft, Industrial Perception, Meka, and Redwood Robotics. James was appointed head of the Robotics division after Andy Rubin's departure from Google in October 2014. In May 2015, James brought together researchers in robotics, computer vision, and machine learning technology within Google Research to help realize the original Cloud Robotics concept.

James started his career as Database Administrator at ASIC Technology and News in 1990. A year later, he joined Microsoft as Software Design Engineer Intern where he worked on MS Excel 4.0. He continued as a Research Assistant at the Stanford Linear Accelerator Center and soon became Graduate Research Assistant where he contributed to a variety of research projects in computer graphics, robotics, haptics, computer vision, and physically-based modeling.

His dissertation research combined robot motion planning with computer graphics to synthesize motion for articulated animated characters from task-level commands. While in Stanford, James was also a Visiting Researcher at Tokyo Institute of Technology and he also at that time cofounded The Motion Factory, where he was the Senior Software Engineer and a member of the engineering team to develop C++-based authoring tools for high-level graphic animation and interactive multimedia content. This company was acquired by SoftImage in 2000.

In the summer of 1999, James became a Postdoctoral Research Fellow at The University of Tokyo where he designed and implemented large-scale simulation and graphic visualization software to facilitate task-based control and autonomous motion planning for humanoid robots.

In 2002, he became AIST Research Fellow at the Digital Human Lab, National Institute of Advanced Industrial Science & Technology (AIST), Tokyo, Japan and stayed there for the next seven years researching efficient models for human simulation and autonomous robot motion.

In May 2007, James founded and became the Director of Robot Autonomy where he coordinated research and software consulting for industrial and consumer robotics applications. In 2008, James assisted in the iOS development of Jiggibo, the first on-phone, real-time speech recognition, translation, and speech synthesis application for the iPhone. This company was acquired by Facebook in 2013. In September 2009, James joined Google.

James is one of the most highly cited authors in the field of Robotics and Motion Planning, with over 15,000 citations. James has published over 125 technical papers and was issued more than 50 patents related to robotics and computer vision technology. James received the Okawa Foundation Award for Young Researchers in 2007.

James coauthored Planning among movable obstacles with artificial constraints, Hierarchical motion planning for self-reconfigurable modular robots, Online environment reconstruction for biped navigation, The experimental humanoid robot H7 : A research platform for autonomous behavior, A unified approach to inverse kinematics and path planning for redundant manipulators, Footstep Planning for the Honda ASIMO Humanoid, and Performance benchmarks for path planning in high dimensions. Read the full list of his publications!

His ongoing research projects are:

Graphical Simulation of Robotic Systems

The goal of this research is to create graphical simulation software for complex robots such as humanoids. Simulated control, 3D perception, motion planning for obstacle avoidance, and algorithms for integrating vision and planning can then be developed and tested safely and at low cost.

Motion Planning for Humanoids

James is interested in developing algorithms to automatically generate motion for tasks such as navigation and footstep planning, object grasping and manipulation, as well as tasks that require full-body dynamically-stable motion planning.

Self-Collision Detection for Complex Articulated Structures

This research aims at developing algorithms for detecting and preventing self-collisions, which occur when one or more of the links of an articulated robot or character model collides with another link.

Classical Path Planning

The goal of this research is to develop practical and efficient algorithms for solving path planning problems in high dimensions. Applications include robotics, assembly analysis, virtual prototyping, pharmaceutical drug design, manufacturing, and computer animation.

Autonomous Animated Characters

In this research, he explores techniques for creating animated characters whose motion is generated automatically from high-level task commands. Applications include virtual reality, video games, web avatars, desktop movie studios, and other real-time virtual human simulations.

James earned his Bachelor of Science degree. (with distinction) in Computer Science from Stanford University in 1993. He earned his Master of Science degree in Computer Science (Systems specialization) from Stanford University in 1995. He earned his Ph.D. in Computer Science from Stanford University in 1999. He was a Postdoctoral Research Fellow at The University of Tokyo, Japan, from 1999 to 2001.

Watch Animation Theatre piece on Behavior Planning. Watch James Kuffner on Motion Planning for Humanoid Robots.

Visit his Google Scholar page, Google AI profile, his Carnegie Mellon University publication page, his JUSTIA patents page, his ReVOLVy page, and his dblp profile.

Visit his Homepage, LinkedIn profile, Toyota profile. Follow him on Facebook, Instagram, and Twitter.






 


Old Bio


James J. Kuffner, Jr., Ph.D. is Assistant Professor, The Robotics Institute, School of Computer Science, Carnegie Mellon University. He is also AIST Research Fellow, Digital Human Lab, National Institute of Advanced Industrial Science & Technology (AIST), Tokyo, Japan.

James coauthored Planning among movable obstacles with artificial constraints, Hierarchical motion planning for self-reconfigurable modular robots, Online environment reconstruction for biped navigation, The experimental humanoid robot H7 : A research platform for autonomous behavior, A unified approach to inverse kinematics and path planning for redundant manipulators, Footstep Planning for the Honda ASIMO Humanoid, and Performance benchmarks for path planning in high dimensions. Read the full list of his publications!

His ongoing research projects are:

Graphical Simulation of Robotic Systems

The goal of this research is to create graphical simulation software for complex robots such as humanoids. Simulated control, 3D perception, motion planning for obstacle avoidance, and algorithms for integrating vision and planning can then be developed and tested safely and at low cost.

Motion Planning for Humanoids

He is interested in developing algorithms to automatically generate motion for tasks such as navigation and footstep planning, object grasping and manipulation, as well as tasks that require full-body dynamically-stable motion planning.

Self-Collision Detection for Complex Articulated Structures

This research aims at developing algorithms for detecting and preventing self-collisions, which occur when one or more of the links of an articulated robot or character model collides with another link.

Classical Path Planning

The goal of this research is to develop practical and efficient algorithms for solving path planning problems in high dimensions. Applications include robotics, assembly analysis, virtual prototyping, pharmaceutical drug design, manufacturing, and computer animation.

Autonomous Animated Characters

In this research, he explores techniques for creating animated characters whose motion is generated automatically from high-level task commands. Applications include virtual reality, video games, web avatars, desktop movie studios, and other real-time virtual human simulations.

James earned a B.S. (with distinction) in Computer Science from Stanford University in 1993. He earned a M.S. in Computer Science (Systems specialization) from Stanford University in 1995. He earned his Ph.D. in Computer Science from Stanford University in 1999. He was a Postdoctoral Research Fellow at The University of Tokyo, Japan, from 1999 to 2001.

Watch Animation Theatre piece on Behavior Planning. Watch James Kuffner on Motion Planning for Humanoid Robots.

Visit his Google Scholar page, Google AI profile, his Carnegie Mellon University publication page, his JUSTIA patents page, his ReVOLVy page, and his dblp profile.

Visit his Homepage, LinkedIn profile, Toyota profile. Follow him on Facebook, Instagram, and Twitter.