Istituto Italiano di Tecnologia, Genova, Italy DIBRIS, Universit`a di Genova, Genoa, Italy
The extremum seeking controlled pipeline for wiggling-based tactile insertion. The instantaneous parameters theta control the pose of the tip of a key through a UR10 robot arm. The strain that the key exerts on the GelSight Mini's gel pad is observed via a displacement of the corners of a tracked patch in the sensor image feed, L_strain. The objective to be minimized is the sum of L_strain plus L_insertion, where L_insertion represents the depth of insertion into the lock. The extremum seeking control seeks to minimize the objective by adjusting the estimate of theta. As is standard in Extremum Seeking Control, theta is a modulated version of its estimate with each parameter modulated at a different frequency. The high pass filter removes the DC component from the objective signal, demodulation determines the slope of the objective's gradient, and the low pass filter averages the feedback signal with greater high-frequency attenuation than the integrator.
Abstract
When humans perform insertion tasks such as inserting a cup into a cupboard, routing a cable, or key insertion, they wiggle the object and observe the process through tactile and proprioceptive feedback. While recent advances in tactile sensors have resulted in tactile-based approaches, there has not been a generalized formulation based on wiggling similar to human behavior. Thus, we propose an extremum-seeking control law that can insert four keys into four types of locks without control parameter tuning despite significant variation in lock type. The resulting model-free formulation wiggles the end effector pose to maximize insertion depth while minimizing strain as measured by a GelSight Mini tactile sensor that grasps a key. The algorithm achieves a 71\% success rate over 120 randomly initialized trials with uncertainty in both translation and orientation. Over 240 deterministically initialized trials, where only one translation or rotation parameter is perturbed, 84\% of trials succeeded. Given tactile feedback at 13 Hz, the mean insertion time for these groups of trials are 262 and 147 seconds respectively.
Paper
Levi Burner, Pavan Mantripragada, Gabriele M. Caddeo, Lorenzo Natale, Cornelia Fermüller, Yiannis Aloimonos