What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
His primary scientific interests are in Artificial intelligence, Computer vision, Wireless sensor network, Robot and Robotics.
His study connects Human–computer interaction and Artificial intelligence.
His Computer vision study integrates concerns from other disciplines, such as Robot end effector and Visual odometry.
His study in Wireless sensor network is interdisciplinary in nature, drawing from both Key distribution in wireless sensor networks, Telecommunications, Real-time computing and Software deployment.
His work in the fields of Robot, such as Robot learning, intersects with other areas such as Flapping.
His Robotics research is multidisciplinary, relying on both Engineering drawing, Toolbox, Control engineering, MATLAB and Robot kinematics.
His most cited work include:
- A tutorial on visual servo control (3039 citations)
- Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor (814 citations)
- A robotics toolbox for MATLAB (712 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Computer vision, Robot, Robotics and Control engineering.
His Artificial intelligence study frequently draws parallels with other fields, such as Field.
His Computer vision research includes elements of Mobile robot navigation, Visual odometry and Robustness.
His work in Robot tackles topics such as Real-time computing which are related to areas like Software deployment and Underwater.
His work in Robotics addresses subjects such as Automation, which are connected to disciplines such as Manufacturing engineering.
The concepts of his Control engineering study are interwoven with issues in Dragline excavator, Control and Control system, Control theory.
He most often published in these fields:
- Artificial intelligence (58.02%)
- Computer vision (34.36%)
- Robot (28.04%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (58.02%)
- Robot (28.04%)
- Computer vision (34.36%)
In recent papers he was focusing on the following fields of study:
Peter Corke mainly investigates Artificial intelligence, Robot, Computer vision, Robotics and Object.
His work carried out in the field of Artificial intelligence brings together such families of science as Task and GRASP.
Peter Corke interconnects Object detection, Machine learning, Probabilistic logic and Human–computer interaction in the investigation of issues within Robot.
His work on Image, Feature, Light field and Pixel is typically connected to Clutter as part of general Computer vision study, connecting several disciplines of science.
His biological study spans a wide range of topics, including Agriculture, Cartesian coordinate robot, Amazon rainforest, Key and Cartesian manipulator.
His Object study combines topics in areas such as Robot kinematics and Set.
Between 2015 and 2021, his most popular works were:
- Visual Place Recognition: A Survey (555 citations)
- The limits and potentials of deep learning for robotics (211 citations)
- Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach (121 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Operating system
His primary scientific interests are in Artificial intelligence, Computer vision, Robot, Robotics and GRASP.
Much of his study explores Artificial intelligence relationship to Task.
His work on Pixel, Visual servoing and Monocular as part of general Computer vision study is frequently linked to Clutter, therefore connecting diverse disciplines of science.
His work deals with themes such as Feature extraction and Feature, which intersect with Visual servoing.
In the subject of general Robot, his work in Mobile robot, Obstacle avoidance and Mobile robot navigation is often linked to Obstacle, thereby combining diverse domains of study.
Peter Corke works mostly in the field of Robotics, limiting it down to topics relating to Human–computer interaction and, in certain cases, Robot end effector and Integrated design.
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