PROJECT TITLE :

A Dynamical System Approach for Softly Catching a Flying Object: Theory and Experiment

ABSTRACT:

Catching a fast flying object is notably difficult as it consists of two tasks: extremely precise estimation of the item's motion and control of the robot's motion. Any little imprecision could lead the fingers to close too abruptly and let the article fly off from the hand before closing. We have a tendency to present a method to beat for sensorimotor imprecision by introducing softness in the catching approach. Soft catching consists of having the robot moves with the object for a brief period of your time, thus as to leave additional time for the fingers to close on the object. We use a dynamic system-primarily based management law to generate the suitable reach and follow motion, which is expressed as a linear parameter varying (LPV) system. We tend to propose a methodology to approximate the parameters of LPV systems using Gaussian mixture models, primarily based on a set of kinematically possible demonstrations generated by an offline optimal control framework. We tend to show theoretically that the resulting DS can intercept the article at the intercept point, at the right time with the specified velocity direction. Stability and convergence of the approach are assessed through Lyapunov stability theory. The proposed method is validated systematically to catch 3 objects that generate elastic contacts and demonstrate vital improvement over a exhausting catching approach.