terça-feira, 8 de abril de 2014

Livro sobre Algoritmos: Planning Algorithms

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Este livro, disponibilizado pelo autor, Steven M. LaValle, em sua página, apresenta de uma forma unificada os diversos tipos de planejamentos de algoritmos. Este assunto é usado em diversas áreas como robótica, controle e automação, inteligência artificial, computação gráfica, etc.. 








Versões completas em pdf:


Partes e capítulos individuais


PART I: INTRODUCTORY MATERIAL
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Chapter 1: Introduction 
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Motivation, examples, applications, high-level planning concepts, overview of the book.
Chapter 2: Discrete Planning 
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Feasible planning, optimal planning, search algorithms, A*, Dijkstra's algorithm, forward search, backward search, bidirectional search, value iteration, logic-based planning, STRIPS, plan graph, planning as satisfiability.
PART II: MOTION PLANNING
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Chapter 3: Geometric Representations and Transformations 
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Polygonal, polyhedral, and semi-algebraic models. Rigid-body transformations, 3D rotations, kinematic chains, Denavit-Hartenberg parameters, kinematic trees, nonrigid transformations.
Chapter 4: The Configuration Space 
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Topological spaces, manifolds, paths. The C-space of rigid bodies, chains of bodies, and trees of bodies. Configuration space. Quaternions. C-space obstacles, closed kinematic chains, algebraic varieties.
Chapter 5: Sampling-Based Motion Planning 
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Metric spaces, measure, random sampling, low-discrepancy sampling, low-dispersion sampling, grids, lattices, collision detection, Rapidly-exploring Random Trees (RRTs), Probabilistic Roadmaps (PRMs), randomized potential fields.
Chapter 6: Combinatorial Motion Planning
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Vertical cell decomposition, shortest-path roadmaps, maximum-clearance roadmaps, cylindrical algebraic decomposition, Canny's algorithm, complexity bounds, Davenport-Schinzel sequences.
Chapter 7: Extensions of Basic Motion Planning 
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Time varying problems, velocity tuning, multiple-robot coordination, hybrid systems, manipulation planning, protein folding, unknotting, closed chains, Random Loop Generator (RLG), coverage planning, optimal motion planning.
Chapter 8: Feedback Motion Planning 
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Navigation functions, smooth manifolds, vector fields, numerical potential functions, optimal navigation functions, compositions of funnels, dynamic programming on continuous spaces.
PART III: DECISION-THEORETIC PLANNING
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Chapter 9: Basic Decision Theory 
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Optimization and probability review, games against nature, Bayesian classification, zero-sum games, nonzero-sum games, Nash equilibria, utility theory, criticisms of decision theory.
Chapter 10: Sequential Decision Theory 
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Sequential games against nature, value iteration, policy iteration, infinite-horizon planning, discounted cost, average cost, reinforcement learning, sequential games.
Chapter 11: Sensors and Information Spaces 
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Information spaces and information mappings, sensing uncertainty, discrete and continuous sensors, POMDPs, Kalman filtering, particle filtering, information spaces in games.
Chapter 12: Planning Under Sensing Uncertainty 
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Value iteration for planning under sensing uncertainty. Robot localization, mapping, navigation, searching, visibility-based pursuit-evasion, manipulation with sensing uncertainty.
PART IV: PLANNING UNDER DIFFERENTIAL CONSTRAINTS
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Chapter 13: Differential Models 
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Kinematic constraints, Dubins car, Reeds-Shepp car, differential drives, a car pulling trailers, phase space, rigid-body dynamics, dynamics of a chain of bodies, Newtonian mechanics, Euler-Lagrange equation, variational principles, Hamilton's equations, differential games.
Chapter 14: Sampling-Based Planning Under Differential Constraints 
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Phase-space obstacles, nonholonomic planning, kinodynamic planning, trajectory planning, reachability analysis, motion primitives, sampling-based planning, Barraquand-Latombe nonholonomic planner, RRTs, feedback planning, plan-and-transform method, path-constrained trajectory planning, gradient-based trajectory optimization.
Chapter 15: System Theory and Analytical Techniques 
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System properties, stability, Lyapunov functions, controllability, STLC, Hamilton-Jacobi-Bellman equation, Pontryagin's maximum principle, Dubins curves, Reeds-Shepp curves, Balkcom-Mason curves, affine control systems, distributions, Frobenius theorem, Chow-Rashevskii theorem, Lie brackets, control Lie algebra, P. Hall basis, steering with piecewise constant inputs, steering with sinusoids.

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