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Bayesian Tactile Exploration for Compliant Docking with Uncertain Shapes
Kris Hauser
Siebel School of Computing and Data Science
Mechanical Science and Engineering
Electrical and Computer Engineering
Coordinated Science Lab
National Center for Supercomputing Applications (NCSA)
Research output
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Keyphrases
Bayesian Approach
100%
Compliant Motion
100%
Contact Point
100%
Coulomb Friction
100%
Docking Site
100%
Hamiltonian Monte Carlo
100%
Human Tactile Perception
100%
Information Gain
100%
Localization Uncertainty
100%
Motion Model
100%
Numerical Experiments
100%
Object Sensor
100%
Object Shape
100%
Planar Shape
100%
Posterior Distribution
100%
Prior Probability
100%
Probabilistic Simulation
100%
Rigid Motion
100%
Robot End-effector
100%
Sensor Readings
100%
Shape Uncertainty
100%
Tactile Exploration
100%
Computer Science
Bayesian Approach
100%
Coulomb Friction
100%
Hamiltonian Monte Carlo
100%
Information Gain
100%
Motion Model
100%
Posterior Distribution
100%
Prior Probability
100%
Robot
100%
Sensor Reading
100%
Engineering
Bayesian Approach
50%
Closed Form
50%
Coulomb Friction
50%
Docks
100%
End Effector
50%
Information Gain
50%
Motion Model
50%
Numerical Experiment
50%
Object Shape
50%
Posterior Distribution
50%
Prior Probability Distribution
50%
Robot
50%
Sensor Reading
50%