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Robust Ballistic Catching: A Hybrid System Stabilization Problem

Markus M. Schill, Martin Buss

Year
2018
Citations
17
Access
Open access

Abstract

This paper addresses a remaining gap between today's academic catching robots and their future in industrial applications: reliable task execution. A novel parameterization is derived to reduce the three-dimensional (3-D) catching problem to 1-D on the ballistic flight path. Vice versa, an efficient dynamical system formulation allows reconstruction of solutions from 1-D to 3-D. Hence, the body of the work in hybrid dynamical systems theory, in particular on the 1-D bouncing ball problem, becomes available for robotic catching. Uniform Zeno asymptotic stability from bouncing ball literature is adapted, as an example, and extended to fit the catching problem. A quantitative stability measure and the importance of the initial relative state between the object and end-effector are discussed. As a result, constrained dynamic optimization maximizes convergence speed while satisfying all kinematic and dynamic limits. Thus, for the first time, a quantitative success-oriented comparison of catching motions becomes available. The feasible and optimal solution is then validated on two symmetric robots autonomously playing throw and catch.

Keywords

Ball (mathematics)Control theory (sociology)RobotKinematicsDynamical systems theoryConvergence (economics)Computer scienceMeasure (data warehouse)Dynamical system (definition)Stability (learning theory)

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