Olov Andersson

618 total citations · 1 hit paper
26 papers, 373 citations indexed

About

Olov Andersson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Olov Andersson has authored 26 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 8 papers in Control and Systems Engineering. Recurrent topics in Olov Andersson's work include Robotic Path Planning Algorithms (12 papers), Reinforcement Learning in Robotics (7 papers) and Robotics and Sensor-Based Localization (6 papers). Olov Andersson is often cited by papers focused on Robotic Path Planning Algorithms (12 papers), Reinforcement Learning in Robotics (7 papers) and Robotics and Sensor-Based Localization (6 papers). Olov Andersson collaborates with scholars based in Sweden, Switzerland and Australia. Olov Andersson's co-authors include Roland Siegwart, Patrick Doherty, Mariusz Wzorek, Takahiro Miki, Frank Mascarich, Mihir Dharmadhikari, Mihir Kulkarni, Shehryar Khattak, Marco Tranzatto and Marco Hutter and has published in prestigious journals such as Quarterly Journal of the Royal Meteorological Society, IEEE Transactions on Robotics and Science Robotics.

In The Last Decade

Olov Andersson

21 papers receiving 356 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

CERBERUS in the DARPA Subterranean Challenge

2022 155 citations Marco Tranzatto, Takahiro Miki et al. Science Robotics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Olov Andersson Sweden	9	179	166	100	75	40	26	373
Wei Jing Singapore	14	249 1.4×	170 1.0×	115 1.1×	63 0.8×	21 0.5×	34	439
Vladimír Kubelka Czechia	12	133 0.7×	244 1.5×	71 0.7×	94 1.3×	46 1.1×	18	383
Mahdi Abolfazli Esfahani Singapore	12	270 1.5×	249 1.5×	66 0.7×	117 1.6×	28 0.7×	21	474
Sam Prentice United States	5	255 1.4×	189 1.1×	69 0.7×	82 1.1×	45 1.1×	5	393
Dirk Holz Germany	12	236 1.3×	209 1.3×	116 1.2×	60 0.8×	32 0.8×	19	390
Matthias Nieuwenhuisen Germany	13	295 1.6×	303 1.8×	119 1.2×	46 0.6×	34 0.8×	27	445
Mikko Lauri Germany	10	181 1.0×	136 0.8×	104 1.0×	78 1.0×	22 0.6×	21	350
Mohammed Rabah South Korea	10	203 1.1×	192 1.2×	115 1.1×	49 0.7×	30 0.8×	19	430
Sai Vemprala United States	8	183 1.0×	117 0.7×	79 0.8×	137 1.8×	16 0.4×	20	387

Countries citing papers authored by Olov Andersson

Since Specialization

Citations

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

Fields of papers citing papers by Olov Andersson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olov Andersson

This figure shows the co-authorship network connecting the top 25 collaborators of Olov Andersson. A scholar is included among the top collaborators of Olov Andersson 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 Olov Andersson. Olov Andersson 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

Lawrance, Nicholas, et al.. (2025). Evaluating machine‐learning models for wind‐speed downscaling from ECMWF‐IFS data. Quarterly Journal of the Royal Meteorological Society. 151(773).

Zhang, Qingwen, Yi Yang, Ling Li, et al.. (2025). HiMo: High-Speed Objects Motion Compensation in Point Clouds. IEEE Transactions on Robotics. 41. 5896–5911.

Welle, Michael C., et al.. (2025). S$^{2}$-Diffusion: Generalizing From Instance-Level to Category-Level Skills in Robot Manipulation. IEEE Robotics and Automation Letters. 10(12). 12995–13002.

Homberger, Timon, et al.. (2025). Flora: Sample-Efficient Preference-Based Rl Via Low-Rank Style Adaptation of Reward Functions. 4789–4796. 1 indexed citations

Oleynikova, Helen, et al.. (2024). COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry. 1730–1737. 12 indexed citations

Andersson, Olov, et al.. (2024). Unified Guidance and Jerk-Level Dynamic Inversion for Accurate Position Control of Hybrid UAVs. IEEE Transactions on Robotics. 41. 708–728. 1 indexed citations

Pantic, Michael, et al.. (2023). Obstacle avoidance using Raycasting and Riemannian Motion Policies at kHz rates for MAVs. 6 indexed citations

Andersson, Olov, et al.. (2023). Material-Agnostic Shaping of Granular Materials with Optimal Transport. 10652–10659.

Mantel, Thomas, et al.. (2023). Resilient Terrain Navigation with a 5 DOF Metal Detector Drone. 10652–10658. 2 indexed citations

10.

Tranzatto, Marco, Takahiro Miki, Mihir Dharmadhikari, et al.. (2022). CERBERUS in the DARPA Subterranean Challenge. Science Robotics. 7(66). eabp9742–eabp9742. 155 indexed citations breakdown →

11.

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

12.

Dugas, Daniel, Olov Andersson, Roland Siegwart, & Jen Jen Chung. (2022). NavDreams: Towards Camera-Only RL Navigation Among Humans. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2504–2511. 7 indexed citations

13.

Pantic, Michael, et al.. (2022). Reactive Motion Planning for Rope Manipulation and Collision Avoidance using Aerial Robots. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 3384–3391. 1 indexed citations

14.

Andersson, Olov. (2020). Learning to Make Safe Real-Time Decisions Under Uncertainty for Autonomous Robots. Linköping studies in science and technology. Dissertations. 8 indexed citations

15.

Andersson, Olov & Patrick Doherty. (2019). Deep RL for autonomous robots: limitations and safety challenges.. The European Symposium on Artificial Neural Networks. 489–495. 3 indexed citations

16.

Andersson, Olov, et al.. (2019). Real-Time Robotic Search using Structural Spatial Point Processes. Uncertainty in Artificial Intelligence. 995–1005. 4 indexed citations

17.

Andersson, Olov, et al.. (2018). Receding-Horizon Lattice-Based Motion Planning with Dynamic Obstacle Avoidance. KTH Publication Database DiVA (KTH Royal Institute of Technology). 4467–4474. 30 indexed citations

18.

Andersson, Olov, Mariusz Wzorek, & Patrick Doherty. (2017). Deep Learning Quadcopter Control via Risk-Aware Active Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 28 indexed citations

19.

Andersson, Olov, Mariusz Wzorek, Piotr Rudol, & Patrick Doherty. (2016). Model-predictive control with stochastic collision avoidance using Bayesian policy optimization. 4597–4604. 30 indexed citations

20.

Andersson, Olov, Fredrik Heintz, & Patrick Doherty. (2015). Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 17 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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