Presentation on theme: "NUS CS5247 Planning Motions with Intention Presented by: Yan Ke."— Presentation transcript:
NUS CS5247 Planning Motions with Intention Presented by: Yan 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.
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
NUS CS5247 Inputs Geometry of the arms Movable object Obstacles together with their locations Initial and goal configuration
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
NUS CS5247 Transit Paths and Transfer Paths Transit Paths: Arms motions that do not move M Transfer Paths: Arms motions that move M
NUS CS5247 Planning Result
NUS CS5247 Generating Transfer and Transit Paths Section 2
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.
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.
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).
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.
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.
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.
NUS CS5247 Human-Arm Kinematics Section 3
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.
NUS CS5247 Arm Posture What do we have? R, ψ, X What do we want? θ, β,α,η
NUS CS5247 Inverse Kinematics Algorithm
NUS CS5247 Illegal Posture Adjustment Claim: εis the only one to violate its limits. Solution: Decrease Φ. Result: wrist position unchanged when Φ decrease.
NUS CS5247 Experimental Result
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.
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.