TY - JOUR
T1 - Robust Ballistic Catching
T2 - A Hybrid System Stabilization Problem
AU - Schill, Markus M.
AU - Buss, Martin
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - 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.
AB - 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.
KW - Catching
KW - contact modeling
KW - dexterous manipulation
KW - manipulation planning
KW - nonprehensile manipulation
UR - http://www.scopus.com/inward/record.url?scp=85055877505&partnerID=8YFLogxK
U2 - 10.1109/TRO.2018.2868857
DO - 10.1109/TRO.2018.2868857
M3 - Article
AN - SCOPUS:85055877505
SN - 1552-3098
VL - 34
SP - 1502
EP - 1517
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
IS - 6
M1 - 8517162
ER -