What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Charles E. Thorpe focuses on Mobile robot, Artificial intelligence, Computer vision, Robot and Human–computer interaction.
His biological study spans a wide range of topics, including Control engineering, Embedded system and Motion planning.
Charles E. Thorpe performs integrative Artificial intelligence and Obstacle research in his work.
His Computer vision research is multidisciplinary, incorporating perspectives in Probabilistic logic and Robotics.
His study in Simulation extends to Robot with its themes.
Charles E. Thorpe usually deals with Human–computer interaction and limits it to topics linked to Teleoperation and Human–robot interaction.
His most cited work include:
- Vision and navigation for the Carnegie-Mellon Navlab (728 citations)
- Simultaneous Localization, Mapping and Moving Object Tracking (478 citations)
- Stereo- and neural network-based pedestrian detection (347 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Computer vision, Mobile robot, Robot and Human–computer interaction are his primary areas of study.
Charles E. Thorpe incorporates Artificial intelligence and Obstacle in his research.
His Object detection, Tracking and Image processing study, which is part of a larger body of work in Computer vision, is frequently linked to Geography, bridging the gap between disciplines.
The Mobile robot study combines topics in areas such as Control engineering, Teleoperation and Motion planning.
The Teleoperation study which covers Embedded system that intersects with Sensor fusion.
His study looks at the relationship between Robot and fields such as Simulation, as well as how they intersect with chemical problems.
He most often published in these fields:
- Artificial intelligence (50.60%)
- Computer vision (39.29%)
- Mobile robot (36.90%)
What were the highlights of his more recent work (between 1998-2013)?
- Artificial intelligence (50.60%)
- Computer vision (39.29%)
- Mobile robot (36.90%)
In recent papers he was focusing on the following fields of study:
Charles E. Thorpe spends much of his time researching Artificial intelligence, Computer vision, Mobile robot, Robot and Teleoperation.
Charles E. Thorpe integrates Artificial intelligence and Obstacle in his studies.
In general Computer vision study, his work on Object detection and Tracking often relates to the realm of Geography, thereby connecting several areas of interest.
His Mobile robot research integrates issues from Value, Image sensor, Human–robot interaction and Human–computer interaction.
His study in the field of Robot control is also linked to topics like Operating environment.
His Teleoperation research incorporates elements of Control engineering, Simulation, Embedded system and Sensor fusion.
Between 1998 and 2013, his most popular works were:
- Simultaneous Localization, Mapping and Moving Object Tracking (478 citations)
- Stereo- and neural network-based pedestrian detection (347 citations)
- Vehicle Teleoperation Interfaces (342 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His main research concerns Artificial intelligence, Computer vision, Mobile robot, Robot and Teleoperation.
His work deals with themes such as Pedestrian detection and Algorithm, which intersect with Artificial intelligence.
The various areas that he examines in his Computer vision study include Artificial neural network and Probabilistic logic.
His research brings together the fields of Real-time computing and Mobile robot.
The concepts of his Teleoperation study are interwoven with issues in Human–robot interaction, Human–computer interaction, Control engineering and Robot control, Social robot.
As a part of the same scientific family, he mostly works in the field of Object detection, focusing on Tracking and, on occasion, Simultaneous localization and mapping, Robotics, Structure and Motion modeling.
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