What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Wolfram Burgard mostly deals with Artificial intelligence, Mobile robot, Robot, Computer vision and Robotics.
Wolfram Burgard has researched Artificial intelligence in several fields, including Algorithm and Machine learning.
Wolfram Burgard interconnects Particle filter, Motion planning and Markov chain in the investigation of issues within Mobile robot.
His Robot research incorporates themes from Grid, Real-time computing, Position and Human–computer interaction.
While the research belongs to areas of Computer vision, Wolfram Burgard spends his time largely on the problem of 3d model, intersecting his research to questions surrounding Surface.
His study in the field of Outline of robotics also crosses realms of Field.
His most cited work include:
- The dynamic window approach to collision avoidance (1879 citations)
- A benchmark for the evaluation of RGB-D SLAM systems (1670 citations)
- Robust Monte Carlo localization for mobile robots (1552 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Robot, Computer vision, Mobile robot and Robotics.
Wolfram Burgard has included themes like Machine learning and Pattern recognition in his Artificial intelligence study.
His Robot study incorporates themes from Task, Real-time computing, Simulation and Human–computer interaction.
His biological study spans a wide range of topics, including Grid, Odometry and Trajectory.
His work deals with themes such as Particle filter, Motion planning and Algorithm, which intersect with Mobile robot.
His Convolutional neural network research incorporates elements of Decoding methods and Deep learning.
He most often published in these fields:
- Artificial intelligence (67.46%)
- Robot (50.40%)
- Computer vision (37.96%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (67.46%)
- Robot (50.40%)
- Computer vision (37.96%)
In recent papers he was focusing on the following fields of study:
Wolfram Burgard spends much of his time researching Artificial intelligence, Robot, Computer vision, Convolutional neural network and Human–computer interaction.
His Artificial intelligence research incorporates themes from Machine learning and Pattern recognition.
His specific area of interest is Robot, where Wolfram Burgard studies Mobile robot.
His Computer vision study combines topics in areas such as Lidar, Visual odometry and Leverage.
The Convolutional neural network study combines topics in areas such as Frame, Decoding methods and Image.
His studies deal with areas such as Ground truth and Probabilistic logic as well as Object.
Between 2016 and 2021, his most popular works were:
- Deep learning with convolutional neural networks for EEG decoding and visualization. (628 citations)
- The limits and potentials of deep learning for robotics (211 citations)
- Deep reinforcement learning with successor features for navigation across similar environments (127 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His primary areas of investigation include Artificial intelligence, Robot, Convolutional neural network, Computer vision and Robustness.
His Robot research includes elements of Leverage, Task, Human–computer interaction, Object and Probabilistic logic.
His Convolutional neural network research is multidisciplinary, relying on both Frame, Decoding methods, Image and Metric.
His study in Computer vision is interdisciplinary in nature, drawing from both Lidar and Mobile robot.
His Mobile robot study combines topics from a wide range of disciplines, such as Street crossing, Generalization, Social force model and Multimodal interaction.
Wolfram Burgard interconnects Image segmentation, Cost efficiency, Robot control, Simulation and Machine learning in the investigation of issues within Robustness.
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