Lars Blackmore

3.0k total citations · 2 hit papers
44 papers, 2.1k citations indexed

About

Lars Blackmore is a scholar working on Aerospace Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lars Blackmore has authored 44 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Aerospace Engineering, 19 papers in Control and Systems Engineering and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lars Blackmore's work include Spacecraft Dynamics and Control (20 papers), Advanced Control Systems Optimization (14 papers) and Space Satellite Systems and Control (9 papers). Lars Blackmore is often cited by papers focused on Spacecraft Dynamics and Control (20 papers), Advanced Control Systems Optimization (14 papers) and Space Satellite Systems and Control (9 papers). Lars Blackmore collaborates with scholars based in United States, United Kingdom and France. Lars Blackmore's co-authors include Behçet Açıkmeşe, Masahiro Ono, Brian Williams, Daniel P. Scharf, Brian C. Williams, John M. Carson, Hui Li, Soon‐Jo Chung, Fred Y. Hadaegh and Brian P. Williams and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and IEEE Transactions on Control Systems Technology.

In The Last Decade

Lars Blackmore

44 papers receiving 2.0k citations

Hit Papers

Minimum-Landing-Error Powered-Descent Guidance for Mars L... 2010 2026 2015 2020 2010 2013 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lars Blackmore United States 20 1.1k 776 607 241 193 44 2.1k
Behçet Açıkmeşe United States 29 2.5k 2.2× 991 1.3× 685 1.1× 132 0.5× 439 2.3× 153 3.6k
Tom Schouwenaars United States 16 829 0.7× 572 0.7× 878 1.4× 107 0.4× 378 2.0× 23 1.5k
Sándor M. Veres United Kingdom 16 236 0.2× 579 0.7× 156 0.3× 300 1.2× 104 0.5× 165 1.2k
Efstathios Bakolas United States 19 551 0.5× 401 0.5× 341 0.6× 124 0.5× 309 1.6× 118 1.3k
Alexander Domahidi Switzerland 21 402 0.4× 1.2k 1.5× 546 0.9× 170 0.7× 164 0.8× 36 2.2k
Alexander B. Kurzhanski Russia 18 431 0.4× 1.1k 1.4× 130 0.2× 253 1.0× 170 0.9× 91 1.8k
Matthias Gerdts Germany 19 302 0.3× 573 0.7× 145 0.2× 72 0.3× 65 0.3× 101 1.3k
Shenmin Song China 25 1.1k 0.9× 1.1k 1.4× 97 0.2× 352 1.5× 331 1.7× 142 1.9k
George Vukovich Canada 25 700 0.6× 990 1.3× 122 0.2× 365 1.5× 158 0.8× 97 1.7k
H. Michalska Canada 19 296 0.3× 2.2k 2.9× 150 0.2× 201 0.8× 187 1.0× 112 2.6k

Countries citing papers authored by Lars Blackmore

Since Specialization
Citations

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

Fields of papers citing papers by Lars Blackmore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lars Blackmore

This figure shows the co-authorship network connecting the top 25 collaborators of Lars Blackmore. A scholar is included among the top collaborators of Lars Blackmore 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 Lars Blackmore. Lars Blackmore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ono, Masahiro, Brian C. Williams, & Lars Blackmore. (2013). Probabilistic Planning for Continuous Dynamic Systems under Bounded Risk. Journal of Artificial Intelligence Research. 46. 511–577. 42 indexed citations
2.
Casoliva, Jordi, et al.. (2012). G-FOLD: A Real-Time Implementable Fuel Optimal Large Divert Guidance Algorithm for Planetary Pinpoint Landing. 1679. 4193. 9 indexed citations
3.
Blackmore, Lars, et al.. (2012). Lossless convexification of control constraints for a class of nonlinear optimal control problems. 10. 5519–5525. 3 indexed citations
4.
Blackmore, Lars, Behçet Açıkmeşe, & John M. Carson. (2012). Lossless convexification of control constraints for a class of nonlinear optimal control problems. Systems & Control Letters. 61(8). 863–870. 65 indexed citations
5.
Mandić, Milan, Behçet Açıkmeşe, David S. Bayard, & Lars Blackmore. (2012). Analysis of the Touch-And-Go Surface Sampling Concept for Comet Sample Return Missions. NASA Technical Reports Server (NASA). 841–855. 2 indexed citations
6.
Broschart, Stephen B., Behçet Açıkmeşe, Milan Mandić, et al.. (2011). GN&C trades for Touch-And-Go sampling at small bodies. NASA Technical Reports Server (NASA). 385–401. 1 indexed citations
7.
Açıkmeşe, Behçet & Lars Blackmore. (2011). Lossless convexification of a class of optimal control problems with non-convex control constraints. Automatica. 47(2). 341–347. 174 indexed citations
8.
Chung, Soon‐Jo, et al.. (2010). Cooperative control with adaptive graph Laplacians for spacecraft formation flying. 4926–4933. 11 indexed citations
9.
Blackmore, Lars, et al.. (2010). Lossless convexification of a class of non-convex optimal control problems for linear systems. 776–781. 4 indexed citations
10.
Blackmore, Lars, Yoshiaki Kuwata, Michael Wolf, et al.. (2010). Global reachability and path planning for planetary exploration with montgolfiere balloons. 8 indexed citations
11.
Elfes, Alberto, K. Reh, P. Beauchamp, et al.. (2010). Implications of wind-assisted aerial navigation for Titan mission planning and science exploration. 1–7. 3 indexed citations
12.
Blackmore, Lars & Masahiro Ono. (2009). Convex Chance Constrained Predictive Control Without Sampling. AIAA Guidance, Navigation, and Control Conference. 111 indexed citations
13.
Blackmore, Lars, et al.. (2008). Active Estimation for Jump Markov Linear Systems. IEEE Transactions on Automatic Control. 53(10). 2223–2236. 68 indexed citations
14.
Blackmore, Lars. (2008). Robust Execution for Stochastic Hybrid Systems. DSpace@MIT (Massachusetts Institute of Technology). 7 indexed citations
15.
Blackmore, Lars. (2008). Robust Path Planning and Feedback Design Under Stochastic Uncertainty. AIAA Guidance, Navigation and Control Conference and Exhibit. 22 indexed citations
16.
Blackmore, Lars, Stanislav Funiak, & Brian Williams. (2007). A combined stochastic and greedy hybrid estimation capability for concurrent hybrid models with autonomous mode transitions. Robotics and Autonomous Systems. 56(2). 105–129. 6 indexed citations
17.
Blackmore, Lars, Stephanie Gil, Seung Chung, & Brian Williams. (2007). Model learning for switching linear systems with autonomous mode transitions. 33. 4648–4655. 19 indexed citations
18.
Blackmore, Lars & Brian Williams. (2007). Optimal, Robust Predictive Control of Nonlinear Systems under Probabilistic Uncertainty using Particles. Proceedings of the ... American Control Conference. 1759–1761. 24 indexed citations
19.
Blackmore, Lars, et al.. (2006). Active Estimation for Switching Linear Dynamic Systems. 137–144. 8 indexed citations
20.
Blackmore, Lars, Stanislav Funiak, & Brian Williams. (2005). Combining stochastic and greedy search in hybrid estimation. National Conference on Artificial Intelligence. 282–287. 8 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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