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Manipulation planning for documented objectsPhD defense
Joseph Mirabel
Institut National Polytechnique Toulouse
February 21, 2017
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Robots in factories
J. Mirabel 2/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
European project: Factory in a Day
Best research teams in Europe in various fields.
J. Mirabel 3/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
European project: Factory in a Day
Best research teams in Europe in various fields.
Goal: make robots affordable to small industries.
J. Mirabel 3/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
European project: Factory in a Day
Best research teams in Europe in various fields.
Goal: make robots affordable to small industries.
13 researchers for 2 days.
J. Mirabel 3/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
European project: Factory in a Day
Best research teams in Europe in various fields.
Goal: make robots affordable to small industries.
13 researchers for 2 days.
J. Mirabel 4/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Manipulation planning for documented objects
J. Mirabel 5/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Example scenario
⇒
J. Mirabel 6/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Reduction property
Solution to a manipulation problem
A sequence of:
transit paths: the robot moves alone,
transfer paths: the robot manipulates an
object.
J. Mirabel 7/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Reduction property
Solution to a manipulation problem
A sequence of:
transit paths: the robot moves alone,
transfer paths: the robot manipulates an
object.
Paths in Placement ∩Grasp can be
approximated by transit and tranfer paths.
J. Mirabel 7/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Reduction property
Solution to a manipulation problem
A sequence of:
transit paths: the robot moves alone,
transfer paths: the robot manipulates an
object.
Paths in Placement ∩Grasp can be
approximated by transit and tranfer paths.
J. Mirabel 7/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
J. Mirabel 8/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Find sequence of tasks to achieve the
goal:
Grasp red box,
Move red box,
Grasp green box,
Move green box,
Put down red box,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning query
Solution found.
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning query
Solution found.
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning query
Solution found.
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning queryNo solution found.
◮ Return failure ?◮ State infeasibility ?◮ Use a different grasping pose ?
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning queryNo solution found.
◮ Return failure ?◮ State infeasibility ?◮ Use a different grasping pose ?
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Task “Grasp red box”
Compute grasping pose
Motion planning queryNo solution found.
◮ Return failure ?◮ State infeasibility ?◮ Use a different grasping pose ?
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art: Combined task and motion planning
Task planner
Motion planner
Start, goal configurationsPath, if found
Needs an interface between the
symbolic and geometric layer:
HPN,
conditional reachability graph,
logical predicates,
. . .
J. Mirabel 9/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Manipulation Planning
J. Mirabel 10/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Manipulation Planning
J. Mirabel 10/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art
Subclasses of problems:
rearrangement planning,
J. Mirabel 11/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art
Subclasses of problems:
rearrangement planning,
navigation among movable obstacles,
J. Mirabel 11/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art
Subclasses of problems:
rearrangement planning,
navigation among movable obstacles,
Dual-arm manipulation,
J. Mirabel 11/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art
Subclasses of problems:
rearrangement planning,
navigation among movable obstacles,
Dual-arm manipulation,
Regrasping,
J. Mirabel 11/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
State of the art
Subclasses of problems:
rearrangement planning,
navigation among movable obstacles,
Dual-arm manipulation,
Regrasping,
. . .
J. Mirabel 11/47 Manipulation planning for documented objects
What problems ?
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm addressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 13/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm addressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 13/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm addressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 13/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Introduction
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm addressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 13/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Table of Contents
1 Constraint graph
Problem modelling
Constraint graph2 Manipulation planning
Foliation
Manipulation planner
Crossed foliation issue3 Continuity in constrained motion planning
Newton Raphson method
The problem
Continuous path projection4 Conclusion
Contributions
PerspectivesJ. Mirabel 14/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Composite robot
Composite robot
Kinematic chain composed of all robots and
objects kinematic chains.
J. Mirabel 15/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Composite robot
Composite robot
Kinematic chain composed of all robots and
objects kinematic chains.
Configuration space
CS = CSPR2 × CSBox × CSDrawer
Robot configuration: q = (qPR2, qbox , qdrawer ) ∈ CS
J. Mirabel 15/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Object in the hand”
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Object in the hand”
Explicit formulation
qbox ← HandPosition(qPR2)
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Object in the hand”
Explicit formulation
qbox ← HandPosition(qPR2)
Implicit formulation
HandPosition(qPR2)−ObjectPosition(qbox) = 0
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Object in the hand”
Explicit formulation
qbox ← HandPosition(qPR2)
Implicit formulation
HandPosition(qPR2)−ObjectPosition(qbox) = 0
f (q) = 0
J. Mirabel 16/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Drawer in the hand”
J. Mirabel 17/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Drawer in the hand”
Explicit formulation
qdrawer ← HandPosition(qPR2) ?
J. Mirabel 17/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Drawer in the hand”
Explicit formulation
qdrawer ← HandPosition(qPR2)
J. Mirabel 17/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Drawer in the hand”
Explicit formulation
qdrawer ← HandPosition(qPR2)
Implicit formulation
HandPosition(qPR2)− DrawerPosition(qdrawer ) = 0
J. Mirabel 17/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
Geometrical problem
depends only
q = (qPR2, qbox , qdrawer )
“Drawer in the hand”
Explicit formulation
qdrawer ← HandPosition(qPR2)
Implicit formulation
HandPosition(qPR2)− DrawerPosition(qdrawer ) = 0
f (q) = 0
J. Mirabel 17/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
“Object in right hand” and “drawer in left hand”
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
“Object in right hand” and “drawer in left hand”
Equilibrium ?
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
“Object in right hand” and “drawer in left hand”
Equilibrium ?Numerical constraint
f (q) = 0
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
“Object in right hand” and “drawer in left hand”
Equilibrium ?Numerical constraint
f (q) = 0
Constraint solver
Given q such that f (q) 6= 0
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Constraints
“Object in the hand”
“Drawer in the hand”
“Object in right hand” and “drawer in left hand”
Equilibrium ?Numerical constraint
f (q) = 0
Constraint solver
Given q such that f (q) 6= 0
→ Find q∗ ∈ CS such that f (q∗) = 0.
J. Mirabel 18/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Equilibrium constraint
Motion planning for humanoid robot
J. Mirabel 19/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Equilibrium constraint
Motion planning for humanoid robot
J. Mirabel 19/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Object documentation
J. Mirabel 20/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Object documentation
Gripper and handle frames
X-axis: grasp axis approach,
Z-axis: possible allowed rotation.
J. Mirabel 20/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Object documentation
Contact and support surfaces
Z-axis: orthogonal to the surface.
J. Mirabel 20/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Object documentation
Numerical constraints: Gripper + Handle
Validation of grasp.
Parametrization of the grasp space.
J. Mirabel 20/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Problem modelling
Object documentation
Numerical constraints: Contact + Support surface
Validation of placement.
Parametrization of the placement space.
J. Mirabel 20/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Manipulation problem
Definition
Robots
Objects
Environment
Initial and goal configurations for robots and objects
J. Mirabel 21/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Manipulation problem
Definition
Robots with end-effectors
Objects
Environment
Initial and goal configurations for robots and objects
J. Mirabel 21/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Manipulation problem
Definition
Robots with end-effectors
Objects with handles and contact surfaces
Environment
Initial and goal configurations for robots and objects
J. Mirabel 21/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Manipulation problem
Definition
Robots with end-effectors
Objects with handles and contact surfaces
Environment with support surfaces
Initial and goal configurations for robots and objects
J. Mirabel 21/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Manipulation problem
Definition
Robots with end-effectors
Objects with handles and contact surfaces
Environment with support surfaces
Constraint graph
Initial and goal configurations for robots and objects
J. Mirabel 21/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
State
J. Mirabel 22/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
State
represents a set of configuration satisfying some constraints,
uses validation constraints.
J. Mirabel 22/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
State
represents a set of configuration satisfying some constraints,
uses validation constraints.
Transition
J. Mirabel 22/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
State
represents a set of configuration satisfying some constraints,
uses validation constraints.
Transition
represents a set of motions from one state to another,
uses parametrization constraints.
J. Mirabel 22/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
grasp: Robot holds the object.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
grasp: Robot holds the object.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
grasp: Robot holds the object.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
grasp: Robot holds the object.
P: Placement parameter (yp, zp, θp) is constant.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph
placement graspP
P
G
G
placement: Object is on the table.
grasp: Robot holds the object.
P: Placement parameter (yp, zp, θp) is constant.
G: Grasp parameter θg is constant.
J. Mirabel 23/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
Available objects
Object A
Object B
Available grippers
Gripper 1
Gripper 2
Constraints
Placement of A,B
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1Available objects
Object B
Available grippers
Gripper 2
Constraints
Placement of B, Grasp A-1
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1Available objects
Object B
Available grippers
Gripper 2
Constraints
Placement of B, Grasp A-1
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
Available objects
Available grippers
Constraints
Grasp A-1, B-2
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
Available objects
Available grippers
Constraints
Grasp A-1, B-2
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
Available objects
Object B
Available grippers
Gripper 2
Constraints
Placement of B, Grasp A-1
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
Available objects
Object A
Object B
Available grippers
Gripper 1
Gripper 2
Constraints
Placement of A,B
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
B-2
Available objects
Object A
Available grippers
Gripper 1
Constraints
Placement of A, Grasp B-2
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
B-2
Available objects
Object A
Available grippers
Gripper 1
Constraints
Placement of A, Grasp B-2
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
B-2
Available objects
Available grippers
Constraints
Grasp A-1, B-2
J. Mirabel 24/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Constraint graph generation
Placement
A-1
A-1, B-2
B-2
A-2
A-2, B-1
B-1
J. Mirabel 25/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Example
J. Mirabel 26/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Constraint graph
Example
J. Mirabel 26/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Table of Contents
1 Constraint graph
Problem modelling
Constraint graph2 Manipulation planning
Foliation
Manipulation planner
Crossed foliation issue3 Continuity in constrained motion planning
Newton Raphson method
The problem
Continuous path projection4 Conclusion
Contributions
PerspectivesJ. Mirabel 27/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Foliation
Constraint graph and configuration space
2 constraints on motion
f : position of the object.
g: grasp of the object.
J. Mirabel 28/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Foliation
Constraint graph and configuration space
2 constraints on motion
f : position of the object.
g: grasp of the object.
placement grasp
J. Mirabel 28/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Foliation
Constraint graph and configuration space
2 constraints on motion
f : position of the object.
g: grasp of the object.
placementf grasp
f
f
g
J. Mirabel 28/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
Rapidly exploring Random Treeusing the constraint graph
placement grasp
Manipulation RRT
qrand = shoot random config()
for each connected components
qnear = nearest neighbor(qrand , cc)
fe, fp = select next state(qnear )
qproj = project(qrand , fe)
qnew = extend(qnear , qproj , fp)
tree.insert node( (qnear , qnew , fp) )
J. Mirabel 29/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
J. Mirabel 30/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Manipulation planner
J. Mirabel 30/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
What about this case ?
⇒
J. Mirabel 31/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
Crossed foliation issue
placement grasp
J. Mirabel 32/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
Crossed foliation issue
placement grasp
The probability that q1proj and q2
proj are on the same
Bgiis zero.
J. Mirabel 32/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
Crossed foliation issue
placement grasp
The probability that q1proj and q2
proj are on the same
Bgiis zero.
Crossed foliation transition
Keep track of the reached leaves.
J. Mirabel 32/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
Results
Joseph Mirabel and Florent Lamiraux, Manipulation planning: addressing the crossed foliation issue, ICRA 2017.
J. Mirabel 33/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Crossed foliation issue
Results
Joseph Mirabel and Florent Lamiraux, Manipulation planning: addressing the crossed foliation issue, ICRA 2017.
J. Mirabel 33/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Table of Contents
1 Constraint graph
Problem modelling
Constraint graph2 Manipulation planning
Foliation
Manipulation planner
Crossed foliation issue3 Continuity in constrained motion planning
Newton Raphson method
The problem
Continuous path projection4 Conclusion
Contributions
PerspectivesJ. Mirabel 34/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Discontinuities
J. Mirabel 35/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Discontinuities
J. Mirabel 35/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
x
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
x
x1
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
x
x1
f(x1)
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
x
x1
f(x1)
x2
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
xx2
f(x2)
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
xx2
f(x2)
x3
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
xx3
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Newton Raphson method
Solving abstract constraints
Find x such that f (x) = 0:
f(x)
x
x1
x2
x3
J. Mirabel 36/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
The problem
Point-wise path projection
− Constraint:
f (x , y) = x2 − 1 = 0
J. Mirabel 37/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
The problem
Point-wise path projection
− Constraint:
f (x , y) = x2 − 1 = 0
− Discretize
J. Mirabel 37/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
The problem
Point-wise path projection
− Constraint:
f (x , y) = x2 − 1 = 0
− Discretize
− Project each sample
J. Mirabel 37/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
The problem
Point-wise path projection
− Constraint:
f (x , y) = x2 − 1 = 0
− Discretize
− Project each sample
J. Mirabel 37/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Newton-Raphson algorithm
Intuition
Discontinuity arises when the constraint Jacobian becomes singular.
J. Mirabel 38/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Newton-Raphson algorithm
Intuition
Discontinuity arises when the constraint Jacobian becomes singular.
Theorem
Let q ∈ CS. If the constraint is not singular in q, then the iteration function is continuous
on a ball of radiusσ(q)
M
where
σ(q) is the smallest singular value of the constraint Jacobian,
M is an upper bound of the norm of the constraint Hessian.
J. Mirabel 38/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Initial path to project
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Continuity ball
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Add sample within continuity ball
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Project sample
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
After one iteration
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Continuity ball
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Add sample within continuity ball
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
Project sample
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
After two iterations
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Progressive path projection algorithm
J. Mirabel 39/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Example
J. Mirabel 40/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Continuous path projection
Example
J. Mirabel 40/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Table of Contents
1 Constraint graph
Problem modelling
Constraint graph2 Manipulation planning
Foliation
Manipulation planner
Crossed foliation issue3 Continuity in constrained motion planning
Newton Raphson method
The problem
Continuous path projection4 Conclusion
Contributions
PerspectivesJ. Mirabel 41/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Result
J. Mirabel 42/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Result
J. Mirabel 42/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm adressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 43/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm adressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 43/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm adressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 43/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Main contributions
Constraint graph: a model of admissible motions,
Manipulation-RRT: an algorithm adressing manipulation problems,
Algorithms to validate the continuity of constrained motions,
Humanoid Path Planner: an open-source motion planning library.
J. Mirabel 43/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Humanoid Path Planner
General purpose motion and manipulation planning library.
J. Mirabel 44/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Humanoid Path Planner
General purpose motion and manipulation planning library.
Main contributors: Florent Lamiraux, Joseph Mirabel.
J. Mirabel 44/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Humanoid Path Planner
General purpose motion and manipulation planning library.
Main contributors: Florent Lamiraux, Joseph Mirabel.
Published in IROS 2016
HPP: a new software for constrained motion planning, Joseph Mirabel et al..
J. Mirabel 44/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Contributions
Humanoid Path Planner
General purpose motion and manipulation planning library.
Main contributors: Florent Lamiraux, Joseph Mirabel.
Published in IROS 2016
HPP: a new software for constrained motion planning, Joseph Mirabel et al..
Used in many other works:◮ Interactive Motion Planning with Contact, Blin et al, IROS 2016.◮ Ballistic motion planning, Campana et al., MIG 2016 and IROS 2016.◮ A gradient-based path optimization method for motion planning, Campana et al., Advanced Robotics 2016.◮ A Versatile and Efficient Pattern Generator for Generalized Legged Locomotion, Carpentier et al., ICRA 2016.◮ Motion Generation for Pulling a Fire Hose by a Humanoid Robot, Ramirez-Alpizar et al., Humanoids 2016.◮ Tuning Interaction in Motion Planning with Contact, Blin et al, RoMan 2016.◮ Manipulation planning: addressing the crossed foliation issue, Mirabel et al., ICRA 2017.
◮ A fast and efficient acyclic contact planner for multiped robots, Tonneau et al., Submitted to IJRR 2016.
◮ Exploiting Structure in Humanoid Motion Planning, Andreas Orthey, PhD Thesis, 2015
J. Mirabel 44/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Perspectives
Robot programing
Using a graphical interface, the
user:
provides models with
documentation,
J. Mirabel 45/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Perspectives
Robot programing
Using a graphical interface, the
user:
provides models with
documentation,
specifies the task in a
supervised process,
J. Mirabel 45/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Perspectives
Robot programing
Using a graphical interface, the
user:
provides models with
documentation,
specifies the task in a
supervised process,
click on “solve” button.
J. Mirabel 45/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Perspectives
Robot programing
Offline
Build a 3D model Set-up planner
Online
Localize objects
(re) Plan path
Execute plan
J. Mirabel 46/47 Manipulation planning for documented objects
Introduction Constraint graph Manipulation planning Continuity in constrained motion planning Conclusion
Perspectives
Thank you !
J. Mirabel 47/47 Manipulation planning for documented objects
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