Difference between revisions of "2006 PlanningAlgorithms"

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* 106. Subhash Suri, Elias Vicari, Peter Widmayer, Simple Robots with Minimal Sensing: From Local Visibility to Global Geometry, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1114-1120, July 22-26, 2007, Vancouver, British Columbia, Canada
 
* 106. Subhash Suri, Elias Vicari, Peter Widmayer, Simple Robots with Minimal Sensing: From Local Visibility to Global Geometry, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1114-1120, July 22-26, 2007, Vancouver, British Columbia, Canada
 
* 107. Davide Bilò, Yann Disser, Matúš Mihalák, Subhash Suri, Elias Vicari, Peter Widmayer, Reconstructing Visibility Graphs with Simple Robots, Proceedings of the 16th International Conference on Structural Information and Communication Complexity, May 25-27, 2009, Piran, Slovenia
 
* 107. Davide Bilò, Yann Disser, Matúš Mihalák, Subhash Suri, Elias Vicari, Peter Widmayer, Reconstructing Visibility Graphs with Simple Robots, Proceedings of the 16th International Conference on Structural Information and Communication Complexity, May 25-27, 2009, Piran, Slovenia
* 108. Samuel Ieong, Nicolas Lambert, Yoav Shoham, Ronen Brafman, Near-optimal Search in Continuous Domains, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1158-1163, July 22-26, 2007, Vancouver, British Columbia, Canada
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* 108. Samuel Ieong, Nicolas Lambert, [[Yoav Shoham]], Ronen Brafman, Near-optimal Search in Continuous Domains, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1158-1163, July 22-26, 2007, Vancouver, British Columbia, Canada
 
* 109. Jason M. O'Kane, Steven M. LaValle, Dominance and Equivalence for Sensor-based Agents, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1655-1658, July 22-26, 2007, Vancouver, British Columbia, Canada
 
* 109. Jason M. O'Kane, Steven M. LaValle, Dominance and Equivalence for Sensor-based Agents, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1655-1658, July 22-26, 2007, Vancouver, British Columbia, Canada
 
* 110. Mokhtar Gharbi, Juan Cortés, Thierry Siméon, Roadmap Composition for Multi-arm Systems Path Planning, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, p.2471-2476, October 10-15, 2009, St. Louis, MO, USA
 
* 110. Mokhtar Gharbi, Juan Cortés, Thierry Siméon, Roadmap Composition for Multi-arm Systems Path Planning, Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, p.2471-2476, October 10-15, 2009, St. Louis, MO, USA

Revision as of 14:40, 13 August 2019

Subject Headings: Planning Algorithm, Planning Under Uncertainty, Discrete Planning.

Notes

Cited By

Quotes

Abstract

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

Table of Contents

  PART I: INTRODUCTORY MATERIAL
  Chapter 1: Introduction
    Motivation, examples, applications, high-level planning concepts, overview of the book.
  Chapter 2: Discrete Planning
    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
  Chapter 3: Geometric Representations and Transformations
    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
   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
    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
    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
    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
    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
  Chapter 9: Basic Decision Theory
    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
    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
   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
    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
  Chapter 13: Differential Models
    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
    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. 
    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. 


References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2006 PlanningAlgorithmsSteven M. LaVallePlanning Algorithms2006