Andrew Lammas

972 total citations
22 papers, 736 citations indexed

About

Andrew Lammas is a scholar working on Ocean Engineering, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Andrew Lammas has authored 22 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Ocean Engineering, 16 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Networks and Communications. Recurrent topics in Andrew Lammas's work include Underwater Vehicles and Communication Systems (18 papers), Robotic Path Planning Algorithms (16 papers) and Maritime Navigation and Safety (8 papers). Andrew Lammas is often cited by papers focused on Underwater Vehicles and Communication Systems (18 papers), Robotic Path Planning Algorithms (16 papers) and Maritime Navigation and Safety (8 papers). Andrew Lammas collaborates with scholars based in Australia, United States and China. Andrew Lammas's co-authors include Karl Sammut, Fangpo He, Zheng Zeng, Youhong Tang, Lian Lian, Amirmehdi Yazdani, Oleg Yakimenko, Somaiyeh MahmoudZadeh, David Powers and Benoı̂t Clément and has published in prestigious journals such as The International Journal of Robotics Research, Ocean Engineering and Robotics and Autonomous Systems.

In The Last Decade

Andrew Lammas

21 papers receiving 710 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Andrew Lammas Australia	12	602	494	207	131	110	22	736
Somaiyeh MahmoudZadeh Australia	15	324 0.5×	298 0.6×	132 0.6×	115 0.9×	125 1.1×	28	558
Qixin Sha China	11	347 0.6×	273 0.6×	137 0.7×	170 1.3×	92 0.8×	27	599
Yushan Sun China	13	310 0.5×	198 0.4×	124 0.6×	175 1.3×	73 0.7×	41	515
Yulei Liao China	17	471 0.8×	159 0.3×	163 0.8×	422 3.2×	116 1.1×	50	803
Bikramaditya Das India	13	376 0.6×	237 0.5×	175 0.8×	150 1.1×	223 2.0×	35	653
Chengke Xiong China	10	321 0.5×	185 0.4×	191 0.9×	127 1.0×	45 0.4×	14	452
Walter Caharija Norway	14	506 0.8×	194 0.4×	180 0.9×	490 3.7×	67 0.6×	27	747
Bruno M. Ferreira Portugal	12	367 0.6×	97 0.2×	147 0.7×	73 0.6×	80 0.7×	59	489
Xinqian Bian China	12	210 0.3×	149 0.3×	133 0.6×	206 1.6×	61 0.6×	77	420
Sankar Nath Shome India	13	136 0.2×	216 0.4×	103 0.5×	197 1.5×	22 0.2×	42	451

Countries citing papers authored by Andrew Lammas

Since Specialization

Citations

This map shows the geographic impact of Andrew Lammas'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 Andrew Lammas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Lammas more than expected).

Fields of papers citing papers by Andrew Lammas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Lammas. 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 Andrew Lammas. The network helps show where Andrew Lammas may publish in the future.

Co-authorship network of co-authors of Andrew Lammas

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Lammas. A scholar is included among the top collaborators of Andrew Lammas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew Lammas. Andrew Lammas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lammas, Andrew, et al.. (2024). Sim-to-real transfer of adaptive control parameters for AUV stabilisation under current disturbance. The International Journal of Robotics Research. 44(3). 407–430. 2 indexed citations

Yazdani, Amirmehdi, Karl Sammut, Oleg Yakimenko, & Andrew Lammas. (2020). Feasibility analysis of using the hp-adaptive Radau pseudospectral method for minimum-effort collision-free docking operations of AUV. Robotics and Autonomous Systems. 133. 103641–103641. 15 indexed citations

Yazdani, Amirmehdi, Karl Sammut, Oleg Yakimenko, & Andrew Lammas. (2019). A survey of underwater docking guidance systems. Robotics and Autonomous Systems. 124. 103382–103382. 107 indexed citations

Yazdani, Amirmehdi, Karl Sammut, Andrew Lammas, Benoı̂t Clément, & Oleg Yakimenko. (2019). Cooperative Guidance System for AUV Docking with an Active Suspended Docking Station. OCEANS 2019 - Marseille. 1–6. 2 indexed citations

Lammas, Andrew, et al.. (2019). Toward the Generation of Mission Plans for Operation of Autonomous Marine Vehicles in Confined Areas. IEEE Journal of Oceanic Engineering. 44(2). 320–330. 2 indexed citations

Yazdani, Amirmehdi, et al.. (2017). IDVD-based trajectory generator for autonomous underwater docking operations. Robotics and Autonomous Systems. 92. 12–29. 39 indexed citations

Zeng, Zheng, Karl Sammut, Lian Lian, et al.. (2017). Rendezvous Path Planning for Multiple Autonomous Marine Vehicles. IEEE Journal of Oceanic Engineering. 43(3). 640–664. 35 indexed citations

Zeng, Zheng, Karl Sammut, Lian Lian, et al.. (2016). A comparison of optimization techniques for AUV path planning in environments with ocean currents. Robotics and Autonomous Systems. 82. 61–72. 116 indexed citations

Hutchinson, S.A., et al.. (2016). Development and testing of the TopCat autonomous surface vessel for the Maritime RobotX Challenge 2016. 2 indexed citations

10.

Yazdani, Amirmehdi, Karl Sammut, Oleg Yakimenko, et al.. (2016). Time and energy efficient trajectory generator for autonomous underwater vehicle docking operations. 7 indexed citations

11.

Zeng, Zheng, Andrew Lammas, Karl Sammut, & Fangpo He. (2015). Long-Range Path Planning for AUV's Exploiting Ocean Energy with Forecasted Currents. International Conference on Robotics and Automation.

12.

Zeng, Zheng, Karl Sammut, Andrew Lammas, Fangpo He, & Youhong Tang. (2015). Imperialist Competitive Algorithm for AUV Path Planning in a Variable Ocean. Applied Artificial Intelligence. 29(4). 402–420. 8 indexed citations

13.

Zeng, Zheng, Lian Lian, Karl Sammut, et al.. (2015). A survey on path planning for persistent autonomy of autonomous underwater vehicles. Ocean Engineering. 110. 303–313. 189 indexed citations

14.

Yazdani, Amirmehdi, Karl Sammut, Andrew Lammas, & Youhong Tang. (2015). Real-time quasi-optimal trajectory planning for autonomous underwater docking. 15–20. 10 indexed citations

15.

Zeng, Zheng, Andrew Lammas, Karl Sammut, Fangpo He, & Youhong Tang. (2014). Shell space decomposition based path planning for AUVs operating in a variable environment. Ocean Engineering. 91. 181–195. 66 indexed citations

16.

Zeng, Zheng, Karl Sammut, Andrew Lammas, Fangpo He, & Youhong Tang. (2014). Efficient Path Re-planning for AUVs Operating in Spatiotemporal Currents. Journal of Intelligent & Robotic Systems. 79(1). 135–153. 57 indexed citations

17.

Zeng, Zheng, et al.. (2014). Path planning for rendezvous of multiple AUVs operating in a variable ocean. 42. 451–456. 14 indexed citations

18.

Zeng, Zheng, Karl Sammut, Fangpo He, & Andrew Lammas. (2012). Efficient path evaluation for AUVs using adaptive B-spline approximation. 1–8. 14 indexed citations

19.

Zeng, Zheng, Andrew Lammas, Karl Sammut, & Fangpo He. (2012). Optimal path planning based on annular space decomposition for AUVs operating in a variable environment. 1–9. 24 indexed citations

20.

Lammas, Andrew, Karl Sammut, & Fangpo He. (2008). Improving navigational accuracy for AUVs using the MAPR Particle Filter. 50. 1–8. 2 indexed citations

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.

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