Solving Motion Planning Problems by Iterative Relaxation of Constraints

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Solving Motion Planning Problems by Iterative
Relaxation of Constraints Osman Burchan Bayazit,
Department of Computer Science, Texas AM
University, http//www.cs.tamu.edu/people/burchanb
Nancy M. Amato (Advisor), Department of Computer
Science, Texas AM University, http//www.cs.tamu.
edu/faculty/amato
Hard Motion Planning Problems
Probabilistic Roadmap Methods Kavraki, Svestka,
Latombe,Overmars 1995
What is Motion Planning?
Configuration Space (C-space)
A space which has the same number of dimensions
as the robots degree of freedom. Each point in
C-Space represents robots different
configuration.
Given an environment (descriptions of moveable
object A and obstacles B), and start and goal
positions of A
Intelligent CAD Applications
Alpha Puzzle
Configuration Space
Roadmap Construction (Pre-processing)
Objective separate the two tubes, one is the
robot, the other is an obstacle
Design Requirement it must be possible to remove
the specified part from GE aircraft engine
without disassembling the rest of the engine
(e.g., change at gate) Motion Planning Problem
the part is the robot, and rest of the engine is
the obstacle
1. Randomly generate configurations (nodes)
- discard nodes that are in collision (collision
check)
C-obst
Find a valid path (continuous sequence of valid
configurations of A) from start to goal
2. Connect pairs of nodes to form roadmap -
simple, deterministic local planner (e.g.,
straightline) - discard paths that are in
collision (collision check)
C-obst
C-obst
C-obst
start
Computational biology chemistry
C-obst
Drug Designfind a path for drug molecule to
reach disease molecule
1. Connect start and goal to roadmap
obstacles
2. Find path in roadmap between start and goal
- regenerate plans for edges in roadmap
Find part remove path
Roadmap
goal
All points in C-Space that correspond to an
infeasible configuration (such as collision with
the environment or out of joint limits) are in a
C-space Obstacle (C-obst). Automated planner
should find a path that does not pass through
such regions.
Automatic Planners are good, but sometimes they
cant find a narrow passage in complex
environments.Our goal is to improve them. We work
in Configuration Space (C-space) and use
Probabilistic Roadmap Methods (PRMs).
Benefit of Motion Planning Usually such
requirements tested with physical mock ups.
Digital testing will save time and costs, and
enable more extensive testing.
Protein Folding find folding pathways