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I. Intro
- Where am I?--Sensors and Methods for Mobile Robot Positioning by J. Borenstein , H. R. Everett , and L. Feng
- Robot Motion Planning by J.C. Latombe (out of print)
- Introduction to AI Robotics by Robin Murphy
- Sensors for Mobile Robots by H. Bart R. Everett
- Computational Principles of Mobile Robotics by Gregory Dudek and Michael Jenkin
- Computational Geometry: Algorithms and Applications by Mark de Berg, Marc van Kreveld, Mark Overmars, Otfried Schwarzkopf
- Computational Geometry in C (Second Edition) by Joseph O'Rourke
- A. Bug2
- 1. Completeness
- 2. Wall Following: Numeric Continuation Methods
- 3. Centerline Sonar Model: distance to closest obstacle
- 4. Does the robot really reach the goal?
- B. TanBug (Rimon)
- C. WedgeBug (Laubach & Burdick)
- D. 3D Bug (Rimon)
- A. Attractive/Repulsive Functions
- 1. Positive Charge Analogy and Hill Climbing
- 2. Distance Function
- Definition and gradient
- Centerline Sonar Model: Distance to all obstacles
- Local Minima in sensor array
- Brushfire algorithm
- 3. Potential Function Definition
- Functional Definition
- Gradient Descent (Minima, maxima, saddle)
- Direct Sensor Measurements
- Vectorfield Histogram (Borenstein)
- Brushfire
- Fast March Algorithm (Sethian (Potential based))
- 4. Combination of Functions (related to behavioral-based)
- Piece-wise potential functions (Arkin/Balch "Aura: Principles and Practices" - adding discrete potential fields)
- B. Local Minimum Problem -- trapped
- C. Adding more forces (Balch/Arkin "Avoiding the past" - method to overcome local minima)
- D. Navigation Functions (Rimon & Kodicheck)
- E. Randomized Potentials??? (Here or probabilistic techniques chap) (Barraquand, Langlois & Latombe)
- A. Polygonal Obstacles (De Berg etc. Chapter 13)
- B. Some higher dims
- A. Search a grid (Advertise Numerical Recipes)
- B. Frontier Exploration
- C. Maybe Borenstein here....? (Borenstein)
- D. Framed Quad-Trees (Stentz)
- A. Visibility Graph
- B. Canny's Roadmap (Canny)
- C. OPP
- 1. Canny & Lin
- 2. Rimon
- D. GVG
- E. Place Maps
- A. Probability Primer (Howie wrote this)
- B. Probabilistic potential functions (??? here or above) (Latombe)
- C. Roadmaps
- D. RRT's
- A. Probability Primer
- B. Occupancy
- C. Hybrid Approaches
- Thrun
- Kortenkamp
- Arras - (finding line segments from collections of points like Hough)
- A. Kalman
- text that howie wrote
- Davison (slam using vision)
- Leonard and Durrante-Whyte
- Guivant (slam - ekf)
- B. Bayesian
- C. Topological Localization
- D. Particle Filter Techniques (Isard Condenstation algorithm for vision)
- Where? (Deans (Invariant Filter))
- A. Trapezoid (Chazzelle or basic thing)
- B. Boustrophedon and Related Approaches
- Acar
- 1. include Bug 2.5 here
- C. Cellular Decompomposition (Collins - (no papers))
- D. Approximate Cell Decomps and Coverage Algos (Butler (where?))
- Arras - (laser and visual homing)
II. Bug Algorithms
III. Configuration Space, Part I
IV. Potential Functions
V. Configuration Space, Part II
VI. Pixel-Based Maps, Part I
VII. Roadmaps
VIII. Probabilistic Motion Planning Techniques
IX. Pixel-Based Maps, Part II
X. Simultaneous Localization and Mapping
XI. Visibility Based
XII. Coverage (Cell Decompositions)
XIII. Non-holonomic Path Planning
XIV. Visual Servoing
XV. Miscellaneous