Planning and Control of Robotic Juggling and Catching Tasks

TLDR

Mirror algorithms generate experimentally observed juggling and catching behavior in a planar robotic mechanism. This article reviews the physical setup and underlying mathematical theory. The authors review the physical setup and theory, then extend the fundamental algorithm to juggling two objects and catching. Mirror algorithms produce experimentally observed juggling and catching; the simplest algorithm is provably correct in a simplified model, and empirical tests confirm the control strategies while suggesting broader implications for robotics.

Abstract

A new class of control algorithms—the "mirror algorithms"— gives rise to experimentally observed juggling and catching behavior in a planar robotic mechanism. The simplest of these algorithms (on which all the others are founded) is provably correct with respect to a simplified model of the robot and its environment. This article briefly reviews the physical setup and underlying mathematical theory. It discusses two significant extensions of the fundamental algorithm to juggling two objects and catching. We provide data from successful empirical verifi cations of these control strategies and briefly speculate on the larger implications for the field of robotics.