Douglas Morrison
Impact in
-
- Robot Manipulation and Learning
-
- Advanced Neural Network Applications
- Advanced Vision and Imaging
Papers in
-
- Robot Manipulation and Learning 5
-
- Advanced Neural Network Applications 2
- Co-authors
- Peter Corke (7 shared papers)Jürgen Leitner (5 shared papers)Gustavo Carneiro (2 shared papers)Michael John Milford (2 shared papers)Sourav Garg (2 shared papers)Ian D. Reid (2 shared papers)Akansel Cosgun (2 shared papers)Tat-Jun Chin (2 shared papers)
- Journals
- The International Journal of Robotics Research (1 paper)IEEE Robotics and Automation Letters (1 paper)Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (2 papers)Figshare (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- AustraliaUnited States
In The Last Decade
Douglas Morrison
10 papers receiving 1.1k citations
Douglas Morrison's Hit Papers
Peers
Comparison fields: 5 of 21
- Control and Systems Engineering 826
- Computer Vision and Pattern Recognition 56
- Aerospace Engineering 51
- Artificial Intelligence 38
- Industrial and Manufacturing Engineering 6
Countries citing papers authored by Douglas Morrison
This map shows the geographic impact of Douglas Morrison's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Douglas Morrison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Douglas Morrison more than expected).
Fields of papers citing papers by Douglas Morrison
This network shows the impact of papers produced by Douglas Morrison. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Douglas Morrison. The network helps show where Douglas Morrison may publish in the future.
Co-authors
The 14 scholars most cited alongside Douglas Morrison, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach Hit paper breakdown → | 2018 | 455 |
| 2 | Learning robust, real-time, reactive robotic grasping Hit paper breakdown → | 2019 | 350 |
| 3 | 2020 | 91 | |
| 4 | 2020 | 83 | |
| 5 | 2019 | 53 | |
| 6 | 2018 | 39 | |
| 7 | 2020 | 33 | |
| 8 | Design of a multi-modal end-effector and grasping system: How integrated design helped win the Amazon Robotics Challenge | 2018 | 7 |
| 9 | Estimating Uncertainty in Instance Segmentation using Dropout Sampling | 2019 | 2 |
| 10 | 2025 | 1 |
About Douglas Morrison
Douglas Morrison is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Industrial and Manufacturing Engineering and Nuclear Energy and Engineering, having authored 10 papers that have together received 1.1k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Robotics and Sensor-Based Localization (2 papers), Advanced Neural Network Applications (2 papers) and Industrial Vision Systems and Defect Detection (1 paper). The work is most often cited by research in Control and Systems Engineering (826 citations), Computer Vision and Pattern Recognition (56 citations), Aerospace Engineering (51 citations), Artificial Intelligence (38 citations) and Industrial and Manufacturing Engineering (6 citations). Douglas Morrison has collaborated with scholars based in Australia and United States. Frequent co-authors include Peter Corke, Jürgen Leitner, Gustavo Carneiro, Michael John Milford, Sourav Garg, Ian D. Reid, Akansel Cosgun, Tat-Jun Chin, Niko Sünderhauf and Feras Dayoub. Their work appears in journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters, Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, Figshare and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.