Uncertainty Reduction Using Dynamics

For assembly tasks parts often have to be oriented before they can be put in an assembly. We present a new approach to parts orienting through the manipulation of pose distributions. Through dynamic simulation we can determine the pose distribution for an object being dropped from an arbitrary height on an arbitrary surface. By varying the drop height and the shape of the support surface we can find the initial conditions that will result in a pose distribution with minimal entropy. We attempt to uniquely orient a part with high probability just by varying the initial conditions. We derive a condition on the pose and velocity of an object in contact with a sloped surface that will allow us to quickly determine the final resting configuration of the object. This condition can then be used to quickly compute the pose distribution. We also show simulation and experimental results which confirm that our dynamic simulator can be used to find the true pose distribution of an object.

Authors

• Mark Moll
• Michael A. Erdmann

Keywords

• Uncertainty
• Belts
• Assembly
• Entropy
• Distributed computing
• Computational modeling
• Robots
• Computer science
• Shape
• Gravity
• Uncertainty Reduction
• Surface Slope
• Minimum Entropy
• Object Pose
• Drop Height
• Object Velocity
• Dynamics Simulations
• Center Of Mass
• Kinetic Energy
• Friction Coefficient
• Phase Space
• Polyhedral
• Electronic Configuration
• Configuration Space
• Multiple Contacts
• Conveyor Belt
• Final Configuration
• Horizontal Surface
• Dual Space
• Identical Orientation
• Capture Region
• High Energy Side
• Increase In Kinetic Energy
• Low Energy Side
• Quasi-static Approximation
• Stable Orientation
• Use Of Motion
• Kinetic Energy Dissipation
• Robotic Arm
• Equations Of Motion