What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Mechanical engineering
Ken Goldberg focuses on Artificial intelligence, Robot, Computer vision, Motion planning and Simulation.
His work deals with themes such as Data collection, GRASP and Polygon, which intersect with Artificial intelligence.
His Robot research includes elements of Grippers, The Internet and Human–computer interaction.
Ken Goldberg works mostly in the field of Computer vision, limiting it down to topics relating to Robustness and, in certain cases, Tension, Surgical scissors, Point and Model predictive control.
His Motion planning research is multidisciplinary, incorporating elements of Markov decision process, Mathematical optimization, Control theory and Configuration space.
His Simulation study combines topics from a wide range of disciplines, such as Kinematics, Stereopsis, Convex optimization, Discretization and Finite-state machine.
His most cited work include:
- Eigentaste: A Constant Time Collaborative Filtering Algorithm (1172 citations)
- A Survey of Research on Cloud Robotics and Automation (489 citations)
- Orienting polygonal parts without sensors (388 citations)
What are the main themes of his work throughout his whole career to date?
Ken Goldberg mainly focuses on Artificial intelligence, Robot, Computer vision, Algorithm and GRASP.
In most of his Artificial intelligence studies, his work intersects topics such as Machine learning.
His research investigates the link between Robot and topics such as Task that cross with problems in Reinforcement learning.
His Computer vision study focuses mostly on Point cloud and Segmentation.
His Algorithm research is multidisciplinary, incorporating perspectives in Upper and lower bounds and Sequence.
The concepts of his GRASP study are interwoven with issues in Cloud computing and Motion planning.
He most often published in these fields:
- Artificial intelligence (39.08%)
- Robot (32.76%)
- Computer vision (16.67%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (39.08%)
- Robot (32.76%)
- Computer vision (16.67%)
In recent papers he was focusing on the following fields of study:
Ken Goldberg mostly deals with Artificial intelligence, Robot, Computer vision, GRASP and Robotics.
His research is interdisciplinary, bridging the disciplines of Machine learning and Artificial intelligence.
His Robot study incorporates themes from Task, Human–computer interaction, Supervisor, Grippers and Algorithm.
The various areas that Ken Goldberg examines in his Computer vision study include Automation and Calibration.
His GRASP research incorporates elements of Heap, Metric, Wrench, Set and Bin.
His Robotics study deals with Cloud computing intersecting with Teleoperation.
Between 2017 and 2021, his most popular works were:
- Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation (195 citations)
- Learning ambidextrous robot grasping policies (147 citations)
- RLlib: Abstractions for Distributed Reinforcement Learning (133 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Mechanical engineering
Artificial intelligence, Robot, Computer vision, Human–computer interaction and Robotics are his primary areas of study.
His biological study spans a wide range of topics, including Supervisor, Machine learning and Folding.
His studies in Robot integrate themes in fields like GRASP, Task, Task analysis, Grippers and Visualization.
Ken Goldberg interconnects Transfer of learning and Calibration in the investigation of issues within Computer vision.
Ken Goldberg combines subjects such as Free space, Bin and Bin picking with his study of Human–computer interaction.
His work investigates the relationship between Robotics and topics such as Code that intersect with problems in Variety and Dynamics.
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