Extremum Seeking Controlled Wiggling for Tactile Insertion
Burner, Levi, Mantripragada, Pavan, Caddeo, Gabriele M., Natale, Lorenzo, Fermüller, Cornelia, Aloimonos, Yiannis
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Oct-3-2024
- Country:
- North America > United States > Maryland (0.15)
- Genre:
- Research Report (0.41)
- Technology: