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NUS CS5247 Planning Motions with Intention Presented by: Yan Ke.

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Presentation on theme: "NUS CS5247 Planning Motions with Intention Presented by: Yan Ke."— Presentation transcript:

1 NUS CS5247 Planning Motions with Intention Presented by: Yan Ke

2 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.

3 NUS CS5247

4 Difficulties  Motion with Intention: Human and robot arms are moving with the intention of completing some task.  Restriction: Neurophysiology.  Grasping and Regrasping: Posture; multiple arms.  PSPACE-hard

5 NUS CS5247 Manipulation Planning Overview Section 1

6 NUS CS5247 Inputs  Geometry of the arms  Movable object  Obstacles together with their locations  Initial and goal configuration

7 NUS CS5247 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

8 NUS CS5247 Transit Paths and Transfer Paths  Transit Paths: Arms motions that do not move M  Transfer Paths: Arms motions that move M

9 NUS CS5247 Planning Result

10 NUS CS5247 Generating Transfer and Transit Paths Section 2

11 NUS CS5247 Overview  The entire manipulation planning can be accomplished by following:  Generate a series of subtasks to achieve the goal configuration.  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.

12 NUS CS5247 Generating Transfer Tasks  Grasp set: All various possible grasps for a certain 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.

13 NUS CS5247 Generating Transfer Tasks  The attached list of grasp assignments are obtained 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).

14 NUS CS5247 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.

15 NUS CS5247 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.

16 NUS CS5247 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.

17 NUS CS5247 Human-Arm Kinematics Section 3

18 NUS CS5247 Neurophysiology  Goal: Determine the arm posture for a human arm given the position and orientation of its hand.  Two experimental result:  Arm and wrist posture are for the most part independent of each other.  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.

19 NUS CS5247 Arm Posture  What do we have?  R, ψ, X  What do we want?  θ, β,α,η

20 NUS CS5247 Inverse Kinematics Algorithm

21 NUS CS5247 Illegal Posture Adjustment  Claim: εis the only one to violate its limits.  Solution: Decrease Φ.  Result: wrist position unchanged when Φ decrease.

22 NUS CS5247 Experimental Result

23 NUS CS5247 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.

24 NUS CS5247 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.

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