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A Mathematical Introduction to Robotic Manipulation
Open accessAbstract
A Mathematical Introduction to Robotic Manipulation presents a mathematical formulation of the kinematics, dynamics, and control of robot manipulators. It uses an elegant set of mathematical tools that emphasizes the geometry of robot motion and allows a large class of robotic manipulation problems to be analyzed within a unified framework. The foundation of the book is a derivation of robot kinematics using the product of the exponentials formula. The authors explore the kinematics of open-chain manipulators and multifingered robot hands, present an analysis of the dynamics and control of robot systems, discuss the specification and control of internal forces and internal motions, and address the implications of the nonholonomic nature of rolling contact are addressed, as well. The wealth of information, numerous examples, and exercises make A Mathematical Introduction to Robotic Manipulation valuable as both a reference for robotics researchers and a text for students in advanced robotics courses.
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Cites
Nonlinear controllability and observability
Hermann, R., & Krener, A. (1977) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1977.1101601 · Cited by 2,374
Cited by
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Zhang, J., & Singh, S. (2014) · Robotics: Science and Systems X · doi:10.15607/rss.2014.x.007 · Cited by 3,303
On-Manifold Preintegration for Real-Time Visual--Inertial Odometry
Forster, C., Carlone, L., Dellaert, F., & Scaramuzza, D. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2016.2597321 · Cited by 1,502
Learning Depth from Monocular Videos Using Direct Methods
Wang, C., Buenaposada, J. M., Zhu, R., & Lucey, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00216 · Cited by 667
Deep visual foresight for planning robot motion
Finn, C., & Levine, S. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2017.7989324 · Cited by 599
IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation
Forster, C., Carlone, L., Dellaert, F., & Scaramuzza, D. (2015) · Robotics: Science and Systems XI · doi:10.15607/rss.2015.xi.006 · Cited by 499
Metadata
- Authors
- Murray, R. M., Li, Z., & Sastry, S. S.
- Venue
- CRC Press eBooks
- Publisher
- CRC Press
- Published
- 2017-12-14
- OpenAlex
- W1564897360
- Cited by
- 6,694
- References
- 1
- FWCI
- 151.43
- Type
- book
- Language
- en
- Open access
- green
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