What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
His main research concerns Computer vision, Artificial intelligence, Mobile robot, Robot and Simultaneous localization and mapping.
His work on Matching as part of general Computer vision study is frequently linked to Metric, therefore connecting diverse disciplines of science.
His study in the field of Octree, Visualization and Reflection mapping is also linked to topics like Image registration and Nondestructive testing.
His Mobile robot research includes themes of Iterative closest point, Coordinate system, Data acquisition, Iterative method and Six degrees of freedom.
His studies deal with areas such as Classifier, Semantic mapping and Object detection as well as Six degrees of freedom.
Andreas Nüchter mostly deals with Motion planning in his studies of Robot.
His most cited work include:
- An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments (490 citations)
- 6D SLAM—3D mapping outdoor environments (354 citations)
- Towards semantic maps for mobile robots (340 citations)
What are the main themes of his work throughout his whole career to date?
Andreas Nüchter mostly deals with Artificial intelligence, Computer vision, Mobile robot, Point cloud and Robot.
His work is dedicated to discovering how Artificial intelligence, Pattern recognition are connected with Cognitive neuroscience of visual object recognition and Robustness and other disciplines.
He has included themes like Simultaneous localization and mapping and Laser, Laser scanning in his Computer vision study.
Andreas Nüchter combines subjects such as Iterative closest point, Motion planning, Classifier, Task and Data acquisition with his study of Mobile robot.
As part of the same scientific family, he usually focuses on Point cloud, concentrating on Trajectory and intersecting with Odometry.
In the field of Robot, his study on Robotic mapping overlaps with subjects such as Semantic memory.
He most often published in these fields:
- Artificial intelligence (67.47%)
- Computer vision (64.46%)
- Mobile robot (33.73%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (67.47%)
- Computer vision (64.46%)
- Point cloud (25.30%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Point cloud, Laser scanning and Mobile mapping.
His Artificial intelligence research integrates issues from Clutter, Detector and Pattern recognition.
The study incorporates disciplines such as Simultaneous localization and mapping and Trajectory in addition to Computer vision.
His research investigates the connection between Simultaneous localization and mapping and topics such as Assisted GPS that intersect with problems in Sonar, Raised-relief map, Mobile robot and Navigation system.
His Point cloud study incorporates themes from Change detection, Segmentation, Computer graphics, Object detection and Voxel.
His research integrates issues of Specular reflection, Orientation, Structured light and Scanner in his study of Laser scanning.
Between 2016 and 2021, his most popular works were:
- Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods (81 citations)
- Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing (25 citations)
- The Peopleremover - Removing Dynamic Objects From 3-D Point Cloud Data by Traversing a Voxel Occupancy Grid. (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His primary scientific interests are in Artificial intelligence, Computer vision, Point cloud, Mobile mapping and Laser scanning.
Andreas Nüchter works in the field of Artificial intelligence, focusing on Robotics in particular.
Computer vision and Cartography are frequently intertwined in his study.
His work carried out in the field of Point cloud brings together such families of science as Simultaneous localization and mapping, Segmentation, Real-time computing and Raised-relief map.
In his research, Occupancy grid mapping, Clutter, Visualization and Change detection is intimately related to Traverse, which falls under the overarching field of Mobile mapping.
As a part of the same scientific study, he usually deals with the Laser scanning, concentrating on Specular reflection and frequently concerns with Identification, Object and Usability.
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