nus cs5247 planning motions with intention presented by: yan ke
TRANSCRIPT
NUS CS5247
Planning Motions Planning Motions with Intentionwith Intention
Presented by: Presented by: Yan KeYan Ke
NUS CS5247
Problem Specification
Task: Generate motions for human or robot arms to complete manipulation tasks.
Goal: Find a collision-free path in configuration space.
Tool: Inverse kinematics algorithm.
Usage: Computer animation.
NUS CS5247
NUS CS5247
Difficulties Motion with Intention: Human and robot arms ar
e moving with the intention of completing some task.
Restriction: Neurophysiology.
Grasping and Regrasping: Posture; multiple arms.
PSPACE-hard
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Manipulation Manipulation Planning OverviewPlanning Overview
Section Section 11
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Inputs
Geometry of the arms
Movable object
Obstacles together with their locations
Initial and goal configuration
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The Stable Space and Grasp Space
Stable space: The set of all configurations where the movable object M is statically stable.
Grasp Space: Arms grasping M and moving it stably.
Grasp Space Stable Space Free Space of the Configuration Space
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Transit Paths and Transfer Paths
Transit Paths: Arms motions that do not move M
Transfer Paths: Arms motions that move M
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Planning Result
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Generating Generating Transfer and Transfer and Transit PathsTransit Paths
Section 2Section 2
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Overview The entire manipulation planning can be
accomplished by following:
① Generate a series of subtasks to achieve the goal configuration.
② Plan a transit or transfer path for each subtasks.
Assumption: Transit tasks can be completed by transit paths; transfer tasks can be completed by transfer paths.
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Generating Transfer Tasks Grasp set: All various possible grasps for a certa
in M.
Grasp assignment: A pair associates with an element in grasp set and an identity of the grasping arm(s).
We first generate the path for M moving alone.
Secondly, we attach each configuration of M with a list of grasp assignment.
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Generating Transfer Tasks The attached list of grasp assignments are obtai
ned by pruning out those no longer possible in the new configuration from the previous configuration.
If somehow we found the list of grasp assignment is empty, then a regrasping is necessary here.
We solve this problem by resetting the list, find all possible of grasp again, and associate them with arm(s).
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Assumptions An arm can attain a grasp with a finite set of
different postures.
All arms not involved in the task is placed elsewhere without blocking the motions of working arms.
If M requires two arms to move, any one of them alone, can hold M stably to allow the other one to move in a transit path.
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Result A motion planning path for M, each configuration
is attached with a list of grasp assignment.
The path is partitioned into several subpaths by regrasping.
Each subpath is a transfer task.
It does not guarantee to find the best path.
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Generating Transit Paths Transit paths are the paths moving the arms.
Connect the initial configuration to the first grasp assignment of the first transfer task.
Connect grasp assignments between different transfer tasks.
Connect the last grasp assignment to the goal configuartion.
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Human-Arm Human-Arm KinematicsKinematics
Section 3Section 3
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Neurophysiology Goal: Determine the arm posture for a human
arm given the position and orientation of its hand.
Two experimental result:
① Arm and wrist posture are for the most part independent of each other.
② Arm posture for pointing is mainly determined by an ST model.
ST model: Can determine shoulder and elbow joint angles given the position of hand.
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Arm Posture
What do we have?
R, ψ, X
What do we want?
θ, β,α,η
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Inverse Kinematics Algorithm
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Illegal Posture Adjustment
Claim: εis the only one to violate its limits.
Solution: Decrease Φ.
Result: wrist position unchanged when Φ decrease.
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Exp
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tal R
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Experimental Result Working environment: C and UNIX.
Time used: three and a half minutes.
Identify the transfer tasks: one and a half minutes.
Different grasp assignments in total: 2600.
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Conclusion A novel approach to solve the multi-arm
manipulation planning problem.
Computation time is unbounded. If no path exist, the algorithm may run forever.
Aim to create a task-level animation package for human motions.