What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Michael Beetz mainly investigates Artificial intelligence, Robot, Computer vision, Human–computer interaction and Mobile robot.
His work is dedicated to discovering how Artificial intelligence, Pattern recognition are connected with RGB color model and other disciplines.
His Robot research includes elements of Software, Representation and Probabilistic logic.
His Computer vision research focuses on subjects like Surface reconstruction, which are linked to Triangle mesh.
He has included themes like Robotics, Motion planning, Service, Personal robot and Knowledge representation and reasoning in his Human–computer interaction study.
The concepts of his Mobile robot study are interwoven with issues in Domain and Task.
His most cited work include:
- Fast Point Feature Histograms (FPFH) for 3D registration (1756 citations)
- Towards 3D Point cloud based object maps for household environments (624 citations)
- Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva (511 citations)
What are the main themes of his work throughout his whole career to date?
Michael Beetz mainly focuses on Artificial intelligence, Robot, Human–computer interaction, Computer vision and Mobile robot.
Artificial intelligence connects with themes related to Machine learning in his study.
His work in Robot addresses subjects such as Plan, which are connected to disciplines such as Control.
Michael Beetz combines subjects such as Ontology, Human–robot interaction, Service, Multimedia and Knowledge base with his study of Human–computer interaction.
Michael Beetz works mostly in the field of Computer vision, limiting it down to topics relating to Pattern recognition and, in certain cases, Facial recognition system.
His study in Mobile robot focuses on Mobile robot navigation, Robot learning and Robot kinematics.
He most often published in these fields:
- Artificial intelligence (66.60%)
- Robot (56.40%)
- Human–computer interaction (37.00%)
What were the highlights of his more recent work (between 2015-2021)?
- Robot (56.40%)
- Human–computer interaction (37.00%)
- Artificial intelligence (66.60%)
In recent papers he was focusing on the following fields of study:
Michael Beetz spends much of his time researching Robot, Human–computer interaction, Artificial intelligence, Task and Object.
His Robot research includes themes of Domain, Probabilistic logic, Set and Plan.
His Human–computer interaction research incorporates elements of Ontology, Human–robot interaction, Mobile robot, Knowledge representation and reasoning and Task analysis.
Michael Beetz is studying Robotics, which is a component of Artificial intelligence.
His research investigates the connection between Task and topics such as Motion that intersect with problems in Container.
His Computer vision study combines topics in areas such as Event, Recall, Cross-validation and Torque sensor.
Between 2015 and 2021, his most popular works were:
- Representations for robot knowledge in the KnowRob framework (79 citations)
- Transferring skills to humanoid robots by extracting semantic representations from observations of human activities (66 citations)
- Know Rob 2.0 — A 2nd Generation Knowledge Processing Framework for Cognition-Enabled Robotic Agents (54 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of investigation include Robot, Human–computer interaction, Artificial intelligence, Task and Knowledge representation and reasoning.
His Robot study integrates concerns from other disciplines, such as Haptic perception, Probabilistic logic, Computer vision and Plan.
The Human–computer interaction study combines topics in areas such as Ontology, Human–robot interaction, Task analysis, Robot control and Workspace.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Set.
His Knowledge representation and reasoning research focuses on Knowledge base and how it connects with Knowledge-based systems, Artificial intelligence, situated approach and Applications of artificial intelligence.
His biological study spans a wide range of topics, including Software, Social robot, Episodic memory and Personal robot.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
