H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 73 Citations 36,527 235 World Ranking 651 National Ranking 9
Electronics and Electrical Engineering D-index 62 Citations 28,289 178 World Ranking 476 National Ranking 20

Research.com Recognitions

Awards & Achievements

2018 - Fellow of the Royal Academy of Engineering (UK)

2010 - Fellow of the Royal Society, United Kingdom

2006 - IEEE Fellow For contributions with application to decentralized data fusion algorithms with application to simulaneous localization and navigation

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Computer network

His main research concerns Artificial intelligence, Computer vision, Mobile robot, Sensor fusion and Sonar. His Artificial intelligence study frequently links to related topics such as Beacon. His research in Computer vision intersects with topics in Mobile robot navigation, Kalman filter, Extended Kalman filter and Remotely operated underwater vehicle.

His Mobile robot research incorporates elements of Data mining, Global Map, Filter and Feature. He interconnects Occupancy grid mapping, Wireless sensor network, Distributed computing and Bayesian probability in the investigation of issues within Sensor fusion. His study in Motion planning is interdisciplinary in nature, drawing from both Computational complexity theory, Key and Metric.

His most cited work include:

  • A new method for the nonlinear transformation of means and covariances in filters and estimators (2794 citations)
  • Simultaneous localization and mapping: part I (2554 citations)
  • A solution to the simultaneous localization and map building (SLAM) problem (2266 citations)

What are the main themes of his work throughout his whole career to date?

Hugh Durrant-Whyte spends much of his time researching Artificial intelligence, Computer vision, Sensor fusion, Mobile robot and Kalman filter. Hugh Durrant-Whyte has included themes like Machine learning and Pattern recognition in his Artificial intelligence study. His Computer vision research includes themes of Mobile robot navigation, Simultaneous localization and mapping, Sonar, Position and Dimensionality reduction.

His Sensor fusion research is multidisciplinary, relying on both Distributed computing, Data mining, Wireless sensor network, Real-time computing and Robustness. His studies deal with areas such as Feature, Motion planning and Information filtering system as well as Mobile robot. Hugh Durrant-Whyte focuses mostly in the field of Kalman filter, narrowing it down to matters related to Inertial navigation system and, in some cases, Inertial measurement unit.

He most often published in these fields:

  • Artificial intelligence (41.33%)
  • Computer vision (24.28%)
  • Sensor fusion (23.70%)

What were the highlights of his more recent work (between 2009-2018)?

  • Artificial intelligence (41.33%)
  • Mobile robot (21.10%)
  • Sensor fusion (23.70%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Artificial intelligence, Mobile robot, Sensor fusion, Computer vision and Algorithm. The various areas that Hugh Durrant-Whyte examines in his Artificial intelligence study include Machine learning and Terrain. His Mobile robot research incorporates themes from Covariance matrix and Motion planning.

His research integrates issues of Kalman filter, Automatic vehicle location and Robustness in his study of Sensor fusion. His study on Computer vision is mostly dedicated to connecting different topics, such as Extended Kalman filter. His Algorithm study combines topics from a wide range of disciplines, such as Information filtering system, Inference, Graphical model, Mathematical optimization and Fisher information.

Between 2009 and 2018, his most popular works were:

  • Multisensor Data Fusion (89 citations)
  • Human-robot communication for collaborative decision making - A probabilistic approach (63 citations)
  • Classification and Semantic Mapping of Urban Environments (62 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer network
  • Machine learning

His primary scientific interests are in Artificial intelligence, Control theory, Algorithm, Motion planning and Sensor fusion. His work deals with themes such as Computer vision and Pattern recognition, which intersect with Artificial intelligence. His biological study spans a wide range of topics, including Distributed algorithm, Real-time computing, Inertial navigation system and Odometry.

His Control theory research includes elements of Simulation, Waypoint, Vehicle control and Autonomous Navigation System. Hugh Durrant-Whyte has researched Motion planning in several fields, including Symmetry, Lie group and Mobile robot. His Sensor fusion research is multidisciplinary, incorporating perspectives in Kalman filter, Extended Kalman filter and Interpolation.

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.

Best Publications

Simultaneous localization and mapping: part I

H. Durrant-Whyte;T. Bailey.
IEEE Robotics & Automation Magazine (2006)

4922 Citations

A new method for the nonlinear transformation of means and covariances in filters and estimators

S. Julier;J. Uhlmann;H.F. Durrant-Whyte.
IEEE Transactions on Automatic Control (2000)

4394 Citations

A solution to the simultaneous localization and map building (SLAM) problem

M.W.M.G. Dissanayake;P. Newman;S. Clark;H.F. Durrant-Whyte.
international conference on robotics and automation (2001)

3581 Citations

A new approach for filtering nonlinear systems

S.J. Julier;J.K. Uhlmann;H.F. Durrant-Whyte.
advances in computing and communications (1995)

2761 Citations

Simultaneous localization and mapping (SLAM): part II

T. Bailey;H. Durrant-Whyte.
IEEE Robotics & Automation Magazine (2006)

2353 Citations

Mobile robot localization by tracking geometric beacons

J.J. Leonard;H.F. Durrant-Whyte.
international conference on robotics and automation (1991)

1877 Citations

Directed Sonar Sensing for Mobile Robot Navigation

John J. Leonard;Hugh F. Durrant-Whyte.
(1992)

1264 Citations

Simultaneous map building and localization for an autonomous mobile robot

J.J. Leonard;H.F. Durrant-Whyte.
intelligent robots and systems (1991)

1124 Citations

Simultaneous Localization and Mapping with Sparse Extended Information Filters

Sebastian Thrun;Yufeng Liu;Daphne Koller;Andrew Y. Ng.
The International Journal of Robotics Research (2004)

973 Citations

Inertial navigation systems for mobile robots

B. Barshan;H.F. Durrant-Whyte.
international conference on robotics and automation (1995)

963 Citations

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