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pro vyhledávání: '"Frey, Kristoffer M."'
Autor:
Frey, Kristoffer M.
Uncertainty-aware planning has long been a recurring goal in robotics. By enabling autonomous systems to explicitly reason about their own uncertainty, desirable behaviors that increase observability and ensure robust constraint satisfaction arise na
Externí odkaz:
https://hdl.handle.net/1721.1/139099
Demand for high-performance, robust, and safe autonomous systems has grown substantially in recent years. These objectives motivate the desire for efficient safety-theoretic reasoning that can be embedded in core decision-making tasks such as motion
Externí odkaz:
http://arxiv.org/abs/2006.01109
As autonomous systems increasingly rely on onboard sensing for localization and perception, the parallel tasks of motion planning and state estimation become more strongly coupled. This coupling is well-captured by augmenting the planning objective w
Externí odkaz:
http://arxiv.org/abs/1908.03790
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 147-151).
The navigation problem for mobile robots
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 147-151).
The navigation problem for mobile robots
Externí odkaz:
http://hdl.handle.net/1721.1/113745
Data association in SLAM is fundamentally challenging, and handling ambiguity well is crucial to achieve robust operation in real-world environments. When ambiguous measurements arise, conservatism often mandates that the measurement is discarded or
Externí odkaz:
http://arxiv.org/abs/1809.09646
Sparsity has been widely recognized as crucial for efficient optimization in graph-based SLAM. Because the sparsity and structure of the SLAM graph reflect the set of incorporated measurements, many methods for sparsification have been proposed in ho
Externí odkaz:
http://arxiv.org/abs/1709.06821