The DOI matches its Crossref record.
Modern Robotics: Mechanics, Planning, and Control
Abstract
This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots. Ideal for self-learning, or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background. Modern Robotics presents the state-of-the-art, screw-theoretic techniques capturing the most salient physical features of a robot in an intuitive geometrical way. With numerous exercises at the end of each chapter, accompanying software written to reinforce the concepts in the book and video lectures aimed at changing the classroom experience, this is the go-to textbook for learning about this fascinating subject.
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Cited by
Yang, Y., Bevan, M. A., & Li, B. (2022) · Advanced Intelligent Systems · doi:10.1002/aisy.202200168 · Cited by 35
Transformer-Based Model for Monocular Visual Odometry: A Video Understanding Approach
Françani, A. O., & Maximo, M. R. O. A. (2023) · arXiv · doi:10.48550/arxiv.2305.06121 · Cited by 38
“This representation follows the ZYX Euler parameterization, which yields the following Euler angles [22]:”
Metadata
- Authors
- Lynch, K. M., & Park, F. C.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2017-05-25
- OpenAlex
- W4399469378
- Cited by
- 1,144
- References
- 0
- FWCI
- 14.27
- Type
- book
- Language
- en
- Open access
- closed
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- Lynch, K. M., & Park, F. C. (2017). Modern Robotics: Mechanics, Planning, and Control. Cambridge University Press eBooks. https://doi.org/10.1017/9781316661239
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.