complexity issues in robot motion planning
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Complexity Issues in Robot Motion Planning. Elif Tosun MTH 353 Final Paper. Overview. Introduction & Motivation Basic Definitions Basic Motion Planning Manipulation Planning Algorithmic Approaches Conclusions. Introduction. - PowerPoint PPT PresentationTRANSCRIPT
Complexity Issues in Robot Motion Planning
Elif TosunMTH 353
Final Paper
Overview
Introduction & MotivationBasic DefinitionsBasic Motion PlanningManipulation PlanningAlgorithmic ApproachesConclusions
Introduction
Motion planning is aimed at providing robots with the capability of deciding automatically which motions to execute in order to achieve their tasks without colliding with other objects in their work space.
Considerations Economic Cost - time, energy, etc. Physical limitations - friction, etc.
Motivation
Robot ApplicationsManufacturingMedical SurgeryMolecular BiologyComputer GraphicsAir & Spacecraft Navigation...
Basic DefinitionsRobot: Mechanical system consisting of one or
more rigid bodies possibly connected by various joints and hinges
Configuration: Position of every point of a robot at a given instance
Degrees of Freedom(DOF): number of dimensions along which the robot can move itself.
More definitions
Workspace: Environment in which the robot moves (2D or 3D)
Configuration space: Space of all configurations of a robot
Free space: configuration space minus the space occupied by obstacles
Basic Motion Planning
Objective: To plan a collision free path of a robot with an arbitrary DOF to a goal position in 2D or 3D avoiding a set of obstacles stationary in space.
Complexity Results
3D version : Robot is a set of linked polyhedra and obstacles are fixed polyhedra in 3D
Complexity: PSPACE-hard when the robot has n links
(due to Reif, proved in 1979) P when the robot has a constant DOF
(due to Schwartz & Sharir, proved in 1983)
Complexity Results
2D version : Robot is a set of linked polygons and obstacles are fixed polygonals objects in 2D
Complexity: PSPACE-hard lower bound
(due to Schwartz & Sharir, proved in 1984)
Manipulation Planning
Objective: To have the robot move around objects in the workspace to reach a final arrangement. (Objects cannot move by themselves)
Games: SOKOBAN PushPush
Sokoban
Objective of Robot:To push boxes into their storage locations without getting himself or boxes stuck.
Rules: Cannot pull, can push only one box at a time
Sokoban
Complexity Result:
Proved to be PSPACE-hardSo all puzzles of this kind (different levels, etc.) are PSPACE-complete
(due to Culberson, 1998)
PushPush
Objective: To push blocks in order to get from an initial position to a final position
Rules: -One block at a time -Block slides the full extent
of available space
PushPush
Complexity Result PushPush is NP-hard in 2D and 3D Proof based on reduction from SAT. Open question
Is it NP-Complete (is it in NP?)OR is it PSPACE-Complete??
Algorithmic Approaches
Complete AlgorithmsProbabilistic AlgorithmsHeuristic Algorithms
Complete Algorithms
Guaranteed to find a free path between two give configurations when exists and report failure otherwise
Deal with connectivity of free space by capturing it on a graph. Cell Decomposition - partition of free space Roadmap Technique - network of curves
Not open for improvements
Probabilistic Algorithms
Trade-off exactness against running timeDon’t guarantee a solution but if exists
very likely to find it relatively quicklyExample: Probabilistic Roadmap
AlgorithmExperimental results show that
computation takes less than a secondUsed in maintenance of aircraft
Heuristic Algorithms
Many work well in practice but offer no performance guarantee
Deal with a grid on configuration space Example 1 : Potential Field Example 2 : Approximate Cell
DecompositionSpace for Improvement
Conclusions
Robot Motion Planning is DIFFICULT!!!Many open problems:
motion planning with uncertainty assembly planning approximation algorithms motion with flexible objects, and many more...
Interest moving from theoretical research to approximation algorithms and applications