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Reaching and Grasping. Reaching control synthetic human arm to reach for object or position in space while possibly avoiding obstacles. Grasping Control synthetic hand and fingers to simulate the supporting of an object. Transporting Move object in space, move hand with object, and
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Reaching and Grasping • Reaching • control synthetic human arm to reach for object or position in space while possibly avoiding obstacles • Grasping • Control synthetic hand and fingers to simulate the supporting of an object • Transporting • Move object in space, • move hand with object, and • use IK to move arm along
Reaching: human-like What is “human-like”? • Experiments: • Planning happens in Cartesian space • Not joint space • Not muslce space • Bell-shaped velocity curves • Obstacle avoidance • low curved sections • Connected by highly curved sections
Reaching: inverse kinematics • Inverse kinematics • End-effector = hand • No sense of “body” • Hard to enforce joint limits • Motions not necessarily human-like • Most often used to enforce constraints once end-effector almost in correct position, e.g., • Foot on ground • Hand at object
Human reach IKAN: http://hms.upenn.edu/software/ik/ik.html Use analytic IK whenever possible • Human motion uses pre-defined planar configurations • Hand orientation determines plane • Use wrist to position hand - independent from arm
First determine plane q1 Solve for angles q2 Orient hand Human reach Given body and goal
Obstacle Avoidance • Path planning • End effector • Intermediate links Goal Obstacles
Obstacle Avoidance 1. Look for global optimal solution • 2. “Reason” from starting position • Greedy algorithm w/backtracking 3. Use precompiled known solutions
Obstacle Avoidance • Genetic algorithm • Search space of possible paths • Evaluate path • Collisions, joint limits, comfort • Minimize: • end-effect path length • maximum acceleration • jerk
Tool Manipulation Gravity Minimize torque? Orient tool for maximum comfort?
P. Lee, S. Wei, J. Zhao, N. Badler, SIGGRAPH 90 Strength Guided Motion “Moving a load to a specified position in space” • Strongly influenced by • Strength • comfort Objective: “to find trajectories, both joint and end-effector, that a human-like linkage would traverse to complete a task.”
P. Lee, S. Wei, J. Zhao, N. Badler, SIGGRAPH 90 Strength Guided Motion Comfort level: maximum torque ratio summed over entire body • Perceived exertion: depends on • Amount of strength required (perceived) • Amount of strength available
P. Lee, S. Wei, J. Zhao, N. Badler, SIGGRAPH 90 Strength Guided Motion Each DoF has two muscle groups: extension and flexion • Each muscle group strength is modeled as a function of • Body position • Anthropometry • Gender • Handedness fatigue • Etc.
P. Lee, S. Wei, J. Zhao, N. Badler, SIGGRAPH 90 Strength Guided Motion • 3 Components • Condition monitor - current state • Path Planning Scheme - IK plus headroom • Rate Control Process - determines joint rates • Motion Strategies • Available torque • Reducing moment • Pull back • Added joint, and jerk
Grasping • Hand-object interaction • Hand: ability for various configurations • Object: lends itself to certain uses (affordances) Regrasping Multiple hand manipulation
Task Planning Simulate vision, memory to identify object in environment Plan path of figure through environment Position figure relative to workspace Use DoFs of figure including arm to reach object Configure hand relative to object to grasp it Use strength of figure to manipulate object