What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Quantum mechanics
- Robot
Vijay Kumar mainly focuses on Robot, Control theory, Mobile robot, Control engineering and Artificial intelligence.
Vijay Kumar combines subjects such as Swarm behaviour, Distributed computing and Control theory with his study of Robot.
His studies in Control theory integrate themes in fields like Kinematics and GRASP.
His Mobile robot study also includes fields such as
- Control system, which have a strong connection to Motion control and Human–computer interaction,
- Decentralised system which connect with Convergence.
His Control engineering research integrates issues from Motion, Aerodynamics, Collision avoidance, Simulation and Grippers.
The Artificial intelligence study combines topics in areas such as Work, Field and Computer vision.
His most cited work include:
- Minimum snap trajectory generation and control for quadrotors (1053 citations)
- Modeling and control of formations of nonholonomic mobile robots (1003 citations)
- A vision-based formation control framework (972 citations)
What are the main themes of his work throughout his whole career to date?
Vijay Kumar focuses on Robot, Artificial intelligence, Control theory, Control engineering and Mobile robot.
The study incorporates disciplines such as Distributed computing and Trajectory in addition to Robot.
His research combines Computer vision and Artificial intelligence.
His study in Control theory is interdisciplinary in nature, drawing from both Kinematics, Nonholonomic system and Motion control.
Vijay Kumar works in the field of Control engineering, focusing on Control theory in particular.
His Mobile robot study frequently links to other fields, such as Real-time computing.
He most often published in these fields:
- Robot (39.50%)
- Artificial intelligence (23.25%)
- Control theory (17.95%)
What were the highlights of his more recent work (between 2016-2021)?
- Robot (39.50%)
- Artificial intelligence (23.25%)
- Distributed computing (8.69%)
In recent papers he was focusing on the following fields of study:
His main research concerns Robot, Artificial intelligence, Distributed computing, Computer vision and Robustness.
His research investigates the link between Robot and topics such as Trajectory that cross with problems in Motion planning.
In his research, Motion capture is intimately related to Global Positioning System, which falls under the overarching field of Artificial intelligence.
His Distributed computing research is multidisciplinary, incorporating perspectives in Artificial neural network and Control.
His Inertial measurement unit research incorporates elements of Odometry and Inertial frame of reference.
He studies Control theory, a branch of Control theory.
Between 2016 and 2021, his most popular works were:
- The grand challenges of Science Robotics (361 citations)
- Counting Apples and Oranges With Deep Learning: A Data-Driven Approach (165 citations)
- Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight (160 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Quantum mechanics
- Statistics
His scientific interests lie mostly in Robot, Artificial intelligence, Computer vision, Distributed computing and Robustness.
His Robot research incorporates themes from Swarm behaviour and Control theory.
His Control theory research includes themes of Quadratic programming, Acceleration and Motion planning.
His Computer vision study deals with Tree intersecting with Point cloud, Pipeline and Semantic feature.
Vijay Kumar has included themes like Control and Control theory in his Distributed computing study.
Vijay Kumar works mostly in the field of Mobile robot, limiting it down to concerns involving Flocking and, occasionally, Telecommunications network.
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