What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Robot
James J. Kuffner mainly investigates Motion planning, Robot, Artificial intelligence, Computer vision and Humanoid robot.
His Motion planning study incorporates themes from Distributed computing, Mathematical optimization and Robot control, Mobile robot.
The concepts of his Mathematical optimization study are interwoven with issues in Random tree and Kinodynamic planning.
His Robot study combines topics from a wide range of disciplines, such as Theoretical computer science and Human–computer interaction.
When carried out as part of a general Artificial intelligence research project, his work on Robot kinematics, Motion and Grasp planning is frequently linked to work in Domain, therefore connecting diverse disciplines of study.
His research in Computer vision intersects with topics in Inverse kinematics and Trajectory.
His most cited work include:
- Randomized kinodynamic planning (2077 citations)
- RRT-connect: An efficient approach to single-query path planning (1879 citations)
- Randomized kinodynamic planning (409 citations)
What are the main themes of his work throughout his whole career to date?
James J. Kuffner mainly focuses on Artificial intelligence, Robot, Computer vision, Motion planning and Humanoid robot.
His Artificial intelligence study combines topics in areas such as Animation and Machine learning.
He interconnects Planner and Human–computer interaction in the investigation of issues within Robot.
His work deals with themes such as Inverse kinematics, Computer graphics and Trajectory, which intersect with Computer vision.
His Motion planning research incorporates elements of Control engineering, Robot kinematics, Mathematical optimization and Motion control.
The various areas that he examines in his Humanoid robot study include Simulation and Robot control, Mobile robot.
He most often published in these fields:
- Artificial intelligence (56.65%)
- Robot (56.07%)
- Computer vision (46.82%)
What were the highlights of his more recent work (between 2012-2017)?
- Artificial intelligence (56.65%)
- Computer vision (46.82%)
- Object (20.23%)
In recent papers he was focusing on the following fields of study:
James J. Kuffner mostly deals with Artificial intelligence, Computer vision, Object, Robot and Computer graphics.
In his research on the topic of Artificial intelligence, Focus is strongly related with Machine learning.
His study in Computer vision is interdisciplinary in nature, drawing from both Lens and Trajectory.
His Object study integrates concerns from other disciplines, such as Data modeling, Database, 3d model and Light field.
His research combines Motion and Robot.
His Motion research includes elements of Automatic control, Motion planning, Navigation function and Motion control.
Between 2012 and 2017, his most popular works were:
- Cloud-based robot grasping with the google object recognition engine (207 citations)
- Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards (192 citations)
- Dynamically Maintaining A Map Of A Fleet Of Robotic Devices In An Environment To Facilitate Robotic Action (96 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Robotics
James J. Kuffner focuses on Artificial intelligence, Computer vision, Real-time computing, Robot and Cloud computing.
In his study, Focus is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence.
James J. Kuffner is studying Object, which is a component of Computer vision.
He has included themes like Light field, 3d model, Information retrieval, Perspective and Trajectory in his Object study.
His Real-time computing research integrates issues from Robotic systems and Service.
James J. Kuffner is interested in Motion planning, which is a field of Robot.
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