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Total Size:
19.2 MB
Info Hash:
DBB21C19263AF65325DC6C1F0567431C27CAC0A7
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Added:
Dec. 18, 2025, 2:57 p.m.
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(Last updated: Dec. 18, 2025, 2:58 p.m.)
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| Farber M. Topology and AI...Aspects of Algorithms for Autonomous Motion 2024.pdf | 19.2 MB |
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NOTE
SOURCE: Farber M. Topology and AI...Aspects of Algorithms for Autonomous Motion 2024
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COVER
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MEDIAINFO
Textbook in PDF format
The task of programming a machine to move autonomously and to make autonomous decisions is one of the major challenges of AI. The algorithms generating autonomous robot motions and autonomous decisions are sections of certain fibre bundles and their complexity and structure can be understood using tools of algebraic topology. The book gives an overview of the current achievements in the field of topological robotics concerned with motion algorithms, and in particular how their complexity depends on the topology of the configuration space of the system and the external conditions. The book is a collection of survey articles written by leading researchers in the fields of mathematics, engineering and computer science, with each chapter surveying a different theme or technique.
Frontmatter
Preface
Autonomous robots, motion algorithms and topology
Equivalent environments and covering spaces for robots
Some geometric and topological data-driven methods in robot motion path planning
Towards control, learning and intelligence in reconfigurable systems
Geometric and topological properties of manifolds in robot motion planning
Equivariant topological complexities
Computing with the TC-canonical class
Motion planning in real projective spaces
Generalized topological complexity and its monoidal version
Robotics and the fundamental group
Geodesic complexity
Farber’s conjecture and beyond
Topological complexity of a map
Distributional topological complexity and LS-category
List of contributors
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