Springer Handbook of Robotics
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Classical robotics suffers from compounding errors, poor scalability to diverse deployment scenarios, and undermodeling issues due to simplified analytical models, limiting its effectiveness to unstructured, dynamic environments.
“This approach suffers from compounding errors, poor scalability to diverse deployment scenarios, and undermodeling issues due to simplified analytical models of physical interactions, limiting its effectiveness to unstructured, dynamic environments (e.g., a house versus a factory line).”
From LeRobot: An Open-Source Library for End-to-End Robot Learning (2026) · cites this paper as Siciliano & Khatib, 2016
Cites
Murphy, R. R., Tadokoro, S., & Kleiner, A. (2016) · Springer Handbooks · doi:10.1007/978-3-319-32552-1_60 · Cited by 135 · see citing works
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Soft robotics: Technologies and systems pushing the boundaries of robot abilities
Laschi, C., Mazzolai, B., & Cianchetti, M. (2016) · Science Robotics · doi:10.1126/scirobotics.aah3690 · Cited by 1,570 · see citing works
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985 · see citing works
Health care robotics: qualitative exploration of key challenges and future directions
Cresswell, K., Cunningham-Burley, S., & Sheikh, A. (2018) · Journal of Medical Internet Research · doi:10.2196/10410 · Cited by 220 · see citing works
A Review of GNSS-Independent UAV Navigation Techniques
Gyagenda, N., Hatilima, J. V., Roth, H., & Zhmud, V. (2022) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2022.104069 · Cited by 190 · see citing works
Directed Acyclic Graph Neural Network for Human Motion Prediction
Li, Q., Chalvatzaki, G., Peters, J., & Wang, Y. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra48506.2021.9561540 · Cited by 29 · see citing works
LeRobot: An Open-Source Library for End-to-End Robot Learning
Cadene, R., Aliberts, S., Capuano, F., Aractingi, M., Zouitine, A., Kooijmans, P., Choghari, J., Russi, M., Pascal, C., Palma, S., et al. (2026) · arXiv · doi:10.48550/arxiv.2602.22818
- Authors
- Stark, M., Schiele, B., & Leonardis, A.
- Affiliations
- University of Naples Federico II (IT)
- Stanford University (US)
- Venue
- Springer Handbooks
- Publisher
- Springer International Publishing
- Published
- 2016
- ISSN
- 2522-8692 (ISSN-L)
- 2522-8706
- OpenAlex
- W4243385754
- Cited by
- 2,122
- References
- 1
- Citations by year
- 2026: 176 · 2025: 221 · 2024: 206 · 2023: 243 · 2022: 250 · 2021: 262 · 2020: 255 · 2019: 216 · 2018: 147 · 2017: 87 · 2016: 13 · 2015: 13 · 2014: 6 · 2013: 5 · 2012: 8
- FWCI
- 2.60
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Springer handbooks (publishedVersion)
- Springer eBooks (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- DIAL (Catholic University of Leuven) (submittedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Industrial Automation and Control Systems
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
- Keywords
- robotic manufacturing cell, machine tool integration, lathe, milling machine, machine vision systems, conveyor systems, monitoring program, production automation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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