Bibliography

8. Bibliography#

[ACC+22]

Michal Adamkiewicz, Timothy Chen, Adam Caccavale, Rachel Gardner, Preston Culbertson, Jeannette Bohg, and Mac Schwager. Vision-only robot navigation in a neural radiance world. IEEE Robotics and Automation Letters, 7(2):4606–4613, 2022. doi:10.1109/LRA.2022.3150497.

[BP66]

Leonard E. Baum and Ted Petrie. Statistical Inference for Probabilistic Functions of Finite State Markov Chains. The Annals of Mathematical Statistics, 37(6):1554 – 1563, 1966. doi:10.1214/aoms/1177699147.

[BM12]

Randal W. Beard and Timothy W. McLain. Small Unmanned Aircraft: Theory and Practice. Princeton University Press, February 2012.

[BK60]

Richard Bellman and Robert Kalaba. Dynamic programming and adaptive processes I: mathematical foundation. IRE Transactions on Automatic Control, AC-5(1):5–10, 1960. doi:10.1109/TAC.1960.6429288.

[Cha23]

Stanley H. Chan. Introduction to Probability for Data Science. Michigan Publishing Services, 2023. ISBN 978-1-60785-747-1. URL: https://probability4datascience.com/index.html.

[CLH+05]

Howie Choset, Kevin M. Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia E. Kavraki, and Sebastian Thrun. Principles of Robot Motion. MIT Press, 2005. ISBN 9780262033275. URL: https://mitpress.mit.edu/9780262033275/principles-of-robot-motion/.

[Del21]

Frank Dellaert. Factor graphs: exploiting structure in robotics. Annual Review of Control, Robotics, and Autonomous Systems, 4:141–166, 2021. doi:10.1146/annurev-control-061520-010504.

[DFBT99]

Frank Dellaert, Dieter Fox, Wolfram Burgard, and Sebastian Thrun. Monte carlo localization for mobile robots. In Proceedings 1999 IEEE International Conference on Robotics and Automation, volume 2, 1322–1328 vol.2. 1999. doi:10.1109/ROBOT.1999.772544.

[DK17]

Frank Dellaert and Michael Kaess. Factor graphs for robot perception. Foundations and Trends® in Robotics, 6(1-2):1–139, 2017. URL: https://www.nowpublishers.com/article/Details/ROB-043, doi:10.1561/2300000043.

[Far08]

Jay A. Farrell. Aided Navigation: GPS with High Rate Sensors. McGraw-Hill, 2008.

[FCDS16]

C. Forster, L. Carlone, F. Dellaert, and D. Scaramuzza. On-manifold preintegration for real-time visual-inertial odometry. IEEE Transactions on Robotics, 2016. doi:10.1109/TRO.2016.2597321.

[GBKL19]

Kanishke Gamagedara, Mahdis Bisheban, Evan Kaufman, and Taeyoung Lee. Geometric controls of a quadrotor uav with decoupled yaw control. In 2019 American Control Conference (ACC), 3285–3290. 2019. doi:10.23919/ACC.2019.8815189.

[GBC16]

Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT Press, 2016. ISBN 9780262035613. URL: https://www.deeplearningbook.org.

[HZ00]

Richard Hartley and Andrew Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2000.

[JBM75]

F. Jelinek, L. Bahl, and R. Mercer. Design of a linguistic statistical decoder for the recognition of continuous speech. IEEE Transactions on Information Theory, 21(3):250–256, 1975. doi:10.1109/TIT.1975.1055384.

[LaV06]

Steven M. LaValle. Planning Algorithms. Cambridge University Press, 2006. ISBN 9780521862059. URL: https://lavalle.pl/planning/.

[LS12]

Todd Lupton and Salah Sukkarieh. Visual-inertial-aided navigation for high-dynamic motion in built environments without initial conditions. IEEE Transactions on Robotics, 28(1):61–76, Feb 2012. doi:10.1109/TRO.2011.2170332.

[LP17]

Kevin M. Lynch and Frank C. Park. Modern Robotics: Mechanics, Planning, and Control. Cambridge University Press, USA, 2017. ISBN 1107156300. URL: http://modernrobotics.org/.

[MSKS04]

Yi Ma, Stefano Soatto, Jana Kosecka, and Shankar S. Sastry. An Invitation to 3-D Vision. Springer, 2004.

[MKC12]

Robert Mahony, Vijay Kumar, and Peter Corke. Multirotor aerial vehicles: modeling, estimation, and control of quadrotor. Robotics and Automation Magazine (RAM), 2012. doi:10.1109/MRA.2012.2206474.

[MST+21]

Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. Nerf: representing scenes as neural radiance fields for view synthesis. Commun. ACM, 65(1):99–106, dec 2021. doi:10.1145/3503250.

[MLS94]

Richard M. Murray, Zexiang Li, and Shankar S. Sastry. A Mathematical Introduction to Robotic Manipulation. CRC Press, 1994.

[Sch66]

Peter Schönemann. A generalized solution of the orthogonal procrustes problem. Psychometrika, 31(1):1–10, March 1966. doi:10.1007/BF02289451.

[SNS11]

Roland Siegwart, Illah Reza Nourbakhsh, and Davide Scaramuzza. Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN 9780262015356. URL: https://mitpress.mit.edu/9780262015356/introduction-to-autonomous-mobile-robots/.

[SSC22]

Cheng Sun, Min Sun, and Hwann-Tzong Chen. Direct voxel grid optimization: super-fast convergence for radiance fields reconstruction. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5449–5459. 2022. doi:10.1109/CVPR52688.2022.00538.

[SB18]

Richard S. Sutton and Andrew G. Barto. Reinforcement Learning: An Introduction. The MIT Press, Cambridge, MA, USA, 2 edition, 2018. ISBN 9780262039246. URL: http://incompleteideas.net/book/the-book-2nd.html.

[TBF05]

Sebastian Thrun, Wolfram Burgard, and Dieter Fox. Probabilistic Robotics. The MIT Press, 2005. ISBN 9780262201629. URL: https://mitpress.mit.edu/9780262201629/probabilistic-robotics/.

[Wat89]

Christopher John Cornish Hellaby Watkins. Learning from delayed rewards. King's College, Cambridge United Kingdom, 1989.

[ZLLS20]

Aston Zhang, Zack Lipton, Mu Li, and Alexander J. Smola. Dive into Deep Learning. d2l.ai, 2020. ISBN 978-1009389433. URL: https://d2l.ai/.