CS 498: Introduction to Planning Algorithms
Fall 2011 Tue/Thu 12:30-1:45 Room 4407 Siebel Center
Registration: 40091 (3 hrs), 40092 (4 hrs) Instructor: Steve LaValle
Office Hours: Tue/Thu 2:00-3:00

A Google translation from Chinese to English of the textbook summary:
Planning is the crystallization of human wisdom, planning issues widely found in people's daily work and life. Now, the planning has been involved in computer science, artificial intelligence, mechanical, mechanics, control theory, game theory, probability theory, graph theory, topology, differential geometry, algebraic geometry and many other modern sciences. "Planning Algorithms" is the author's years of teaching and research summary, a systematic introduction to the basics of planning areas and the latest results. The author of three independent disciplines: robotics, artificial intelligence and cybernetics cleverly combined. "Planning algorithm" gives a lot of informative examples to have been relatively difficult to understand the mathematical problem becomes to life, after-school reading references and exercises is to further deepen and expand the reader's understanding of appropriate content.

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Course Calendar (tentative):

Class # Date Lecture Topic Reading Assignments
Week 1
1 8/23 course overview
Ch. 1
2 8/25 discrete feasible planning; search algorithms
Sec. 2.1, 2.2
Week 2
3 8/30 geometric representations; transformations
Sec. 3.1,3.2
4 9/1 transformations, topological concepts
Sec. 3.2,4.1
Week 3
5 9/6 topological concepts
Sec. 4.1.1HW1 Assigned
6 9/8 manifolds
Sec. 4.1.2
Week 4
7 9/13manifolds, C-space
Sec. 4.2,4.3.1
8 9/15 C-space, C-space obstacles
Sec. 4.3.2HW1 Due
Week 5
9 9/20 C-space obstacles
Sec. 4.3.2
10 9/22 metric spaces
Sec. 5.1.1, 5.1.2
Week 6
11 9/27 sampling theory, collision detection
Sec. 5.2, 5.3HW 2 Assigned
12 9/29 collision detection, incremental sampling and searching
Sec. 5.3, 5.4
Week 7
13 10/4 incremental sampling and searching, RRTs
Sec. 5.4, 5.5
14 10/6 RRTs, roadmap methods
Sec. 5.6
Week 8
15 10/11 combinatorial motion planning, polygonal obstacles
Sec. 6.1, 6.2HW 2 Due
16 10/13 Midterm Exam
.
Week 9
1710/18 CLASS CANCELLED
.HW 3 Assigned
18 10/20 vector fields, differential constraints
Sec 8.3.1, 13.1
Week 10
19 10/25 differential constraints
Sec. 13.1.
20 10/27 car-like robots; differential drive
Sec. 13.1
Week 11
21 11/1 phase space, double integrator, particle motions
Sec. 13.2.1, 13.3.2.
22 11/3 motion planning with differential constraints
Sec. 14.1
Week 12
23 11/8 sampling the control space; incremental sampling and searching
Sec. 14.2, 14.3HW 3 Due
24 11/10 incremental sampling and searching
Sec. 14.3,14.4
Week 13
25 11/15 physical sensors, virtual sensors
Sec. 2 and 3 of thisHW 4 Assigned
26 11/17 virtual sensor models
Sec. 3 of this
Thanksgiving Break

Week 14
27 11/29 more virtual sensors; sensor lattice
Sec. 3 of this
28 12/1 spatial and temoporal filtering
Sec. 4 of this
Week 15
29 12/6 planning in information spaces
Sec. 5 of thisHW 4 Due



Homework Assignments

Topics
(estimated number of lectures given):


Textbook: Readings above are from Planning Algorithms, S. M. LaValle, Cambridge University Press, 2006. Also available for free download at http://planning.cs.uiuc.edu/.


Course Mechanics