Planning for Humanoid Robots Presented by Irena Pashchenko CS326a, Winter 2004.
CS 326A: Motion Planning robotics.stanford.edu/~latombe/cs326/2004/index.htm Jean-Claude Latombe Computer Science Department Stanford University.
Sampling and Searching Methods for Practical Motion Planning Algorithms Anna Yershova Dept. of Computer Science University of Illinois.
Tree-Based Planning
Navigation & Motion Planning
Probabilistic Roadmap
Probabilistic Roadmaps
NUS CS 5247 David Hsu1 Last lecture Multiple-query PRM Lazy PRM (single-query PRM)
Robust Combination of Local Controllers
Navigation & Motion Planning Cell Decomposition Skeletonization Bounded Error Planning (Fine-motion Planning) Landmark-based Planning Online Algorithms.
Sampling-Based Planners. The complexity of the robot’s free space is overwhelming.