manipulation planning a geometrical formulation
DESCRIPTION
Manipulation Planning A Geometrical Formulation. Manipulation Planning. Hanoï Tower Problem. Manipulation Planning. Hanoï Tower Problem: a “pure” combinatorial problem. Finite state space. Manipulation Planning. A disk manipulating another disk. Manipulation Planning. - PowerPoint PPT PresentationTRANSCRIPT
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Planning
A Geometrical Formulation
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Planning
• Hanoï Tower Problem
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Planning
• Hanoï Tower Problem: a “pure” combinatorial problem
Finite state space
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Planning
• A disk manipulating another disk
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Planning
• A disk manipulating another disk
The state space is no more finite!
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Space
• Any solution appears a collision-free path in the composite space (CSRobot CSObject )Admissible
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• However: any path in (CSRobot CSObject )Admissible is not necessarily a manipulation path
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation Space
• Any solution appears a collision-free path in the composite space (CSRobot CSObject )Admissible
• What is the topological structure of the manipulation space?
• How to translate the continuous problem into a combinatorial one?
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• Any solution appears a collision-free path in the composite space (CSRobot CSObject )Admissible
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
A work example
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
A work example
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Allowed configurations
• Grasp
• Placement
• Not allowed
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Allowed configurations
• Grasp Space GS
• Placement Space PS
• Manipulation SpaceGS PS
U
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Allowed paths
• Transit paths
• Transfer paths
• Not allowed paths
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Allowed paths induce foliations in GS PS
• Transit paths
• Transfer paths
• Not allowed paths
U
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space topology
UGS PS
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IGS PS
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space topology
UGS PS
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IGS PS
Adjacency by transfer paths
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space topology
UGS PS
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IGS PS
Adjacency by transit paths
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space graph
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Topological property in GS PS
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Theorem: When two foliations intersect, any path can be approximated by paths along both foliations.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Corollary: Paths in GSPS can be approximated by finite sequences of transit and transfer paths
Topological property in GS PS
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space graph
Corollary: A manipulation path exists iff both starting and goal configurations can be retracted on two connected nodes of the manipulation graph.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space graph
Proof
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation space
Transit Path Transit Path
Transit PathTransfer Path
GSPS Path
GSPS Path
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
Manipulation algorithms
• Capturing the topology of GS PS
• Compute adjacency
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
The case of finite grasps and placements
• Graph search
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
The case of two disks
• Capturing the topology of GS PS: projection of the cell decomposition of the composite space
• Adjacency by retraction
B. Dacre Wright, J.P. Laumond, R. Alami Motion planning for a robot and a movable object amidst polygonal obstacles.
IEEE International Conference on Robotics and Automation, Nice,1992.
J. Schwartz, M. SharirOn the Piano Mover III
Int. Journal on Robotics Research, Vol. 2 (3), 1983
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
The general case
• Capturing the topology of GS PS
• Compute adjacency
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
The general case
• Capturing the topology of GS PS:Path planning for closed chain systems
• Compute adjacencyInverse kinematics
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
The general case: probabilistic algorithms
T. Siméon, J.P. Laumond, J. Cortes, A. SahbaniManipulation planning with probabilistic roadmaps
Int. Journal on Robotics Research, Vol. 23, N° 7-8, 2004.
J. Cortès, T. Siméon, J.P. LaumondA random loop generator for planning motions of closed chains with PRM methods
IEEE Int. Conference on Robotics and Automation, Nice, 2002.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
J. Cortès, T. Siméon, J.P. LaumondA random loop generator for planning motions of closed chains with PRM methods
IEEE Int. Conference on Robotics and Automation, Nice, 2002.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
C. Esteves, G. Arechavaleta, J. Pettré, J.P. LaumondAnimation planning for virtual mannequins cooperation
ACM Trans. on Graphics, Vol. 25 (2), 2006.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
E. Yoshida, M. Poirier, J.P. Laumond, O. Kanoun, F. Lamiraux, R. Alami, K. YokoiPivoting based manipulation by a humanoid robot
Autonomous Robots, Vol. 28 (1), 2010.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g
E. Yoshida, M. Poirier, J.-P. Laumond, O. Kanoun, F. Lamiraux, R. Alami, K. YokoiRegrasp Planning for Pivoting Manipulation by a Humanoid Robot IEEE International Conference on Robotics and Automation, 2009.
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J . P . L a u m o n d L A A S – C N R S
M a n i p u l a t i o n P l a n n i n g