Lukas Schmid

638 total citations
11 papers, 423 citations indexed

About

Lukas Schmid is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Ecology. According to data from OpenAlex, Lukas Schmid has authored 11 papers receiving a total of 423 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Aerospace Engineering and 2 papers in Ecology. Recurrent topics in Lukas Schmid's work include Robotics and Sensor-Based Localization (7 papers), Robotic Path Planning Algorithms (6 papers) and Remote Sensing in Agriculture (2 papers). Lukas Schmid is often cited by papers focused on Robotics and Sensor-Based Localization (7 papers), Robotic Path Planning Algorithms (6 papers) and Remote Sensing in Agriculture (2 papers). Lukas Schmid collaborates with scholars based in Switzerland, United States and Australia. Lukas Schmid's co-authors include Roland Siegwart, Juan Nieto, Raghav Khanna, Lionel Ott, Michael Pantic, Olov Andersson, César Cadena, Nathan Matsuda, Achim Walter and Frank Liebisch and has published in prestigious journals such as Optics Express, IEEE Robotics and Automation Letters and Plant Methods.

In The Last Decade

Lukas Schmid

11 papers receiving 407 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lukas Schmid Switzerland	9	273	213	40	39	38	11	423
Jorge Fuentes-Pacheco Mexico	5	454 1.7×	456 2.1×	40 1.0×	39 1.0×	24 0.6×	12	671
Guili Xu China	12	397 1.5×	308 1.4×	26 0.7×	37 0.9×	14 0.4×	65	612
Kaixuan Wang China	10	319 1.2×	223 1.0×	14 0.3×	51 1.3×	29 0.8×	37	430
Yaochen Li China	12	300 1.1×	74 0.3×	75 1.9×	20 0.5×	37 1.0×	66	513
Jared Strader United States	10	164 0.6×	199 0.9×	46 1.1×	38 1.0×	8 0.2×	16	364
Li Su China	12	166 0.6×	97 0.5×	39 1.0×	23 0.6×	15 0.4×	53	361
José‐Joel González‐Barbosa Mexico	10	198 0.7×	149 0.7×	27 0.7×	51 1.3×	14 0.4×	56	401
Xiaohu Zhang China	14	329 1.2×	165 0.8×	46 1.1×	118 3.0×	18 0.5×	56	659
Peng Chang China	12	290 1.1×	119 0.6×	69 1.7×	84 2.2×	14 0.4×	29	463
Juan Irving Vasquez-Gomez Mexico	12	377 1.4×	397 1.9×	18 0.5×	57 1.5×	19 0.5×	31	545

Countries citing papers authored by Lukas Schmid

Since Specialization

Citations

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

Fields of papers citing papers by Lukas Schmid

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Schmid

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

All Works

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11 of 11 papers shown

1.

Maggio, Dominic, et al.. (2024). Clio: Real-Time Task-Driven Open-Set 3D Scene Graphs. IEEE Robotics and Automation Letters. 9(10). 8921–8928. 16 indexed citations

2.

Schmid, Lukas, et al.. (2024). Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments. 14 indexed citations

3.

Müller, Marcus, et al.. (2024). Traversing Mars: Cooperative Informative Path Planning to Efficiently Navigate Unknown Scenes. IEEE Robotics and Automation Letters. 10(2). 1776–1783. 1 indexed citations

4.

Schmid, Lukas, et al.. (2023). Dynablox: Real-Time Detection of Diverse Dynamic Objects in Complex Environments. IEEE Robotics and Automation Letters. 8(10). 6259–6266. 34 indexed citations

5.

Schmid, Lukas, et al.. (2022). Fast and Compute-efficient Sampling-based Local Exploration Planning via Distribution Learning. arXiv (Cornell University). 17 indexed citations

6.

Blum, Hermann, et al.. (2022). Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning. IEEE Robotics and Automation Letters. 7(4). 8691–8698. 19 indexed citations

7.

Schmid, Lukas, Victor Reijgwart, Lionel Ott, et al.. (2021). A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments Under Severe Odometry Drift. IEEE Robotics and Automation Letters. 6(3). 4504–4511. 24 indexed citations

8.

Schmid, Lukas, Michael Pantic, Raghav Khanna, et al.. (2020). An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments. IEEE Robotics and Automation Letters. 5(2). 1500–1507. 193 indexed citations

9.

Khanna, Raghav, Lukas Schmid, Achim Walter, et al.. (2019). A spatio temporal spectral framework for plant stress phenotyping. Plant Methods. 15(1). 13–13. 40 indexed citations

10.

Digumarti, Sundara Tejaswi, Lukas Schmid, G. Rizzi, et al.. (2019). An Approach for Semantic Segmentation of Tree-like Vegetation. 1801–1807. 7 indexed citations

11.

Schmid, Lukas, Nathan Matsuda, Leonidas Spinoulas, et al.. (2015). High spatio-temporal resolution video with compressed sensing. Optics Express. 23(12). 15992–15992. 58 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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