TY - GEN
T1 - Dynamic Primitives and Optimal Feedback Control for the Manipulation of Complex Objects
AU - Razavian, Reza Sharif
AU - Bazzi, Salah
AU - Nayeem, Rashida
AU - Sadeghi, Mohsen
AU - Sternad, Dagmar
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Modern computer algorithms easily beat world champions in chess or Go, but state-of-the-art robots are still outperformed by two-year-old's in manipulating the pieces, let alone interacting with more complex objects. This work studied human behavior when moving an underactuated object, a cup with a ball rolling inside creating internal dynamics like sloshing coffee in a cup. The objective was to develop a control model that could replicate human behavior. Human movement data were collected for transporting this cup-and-ball system, both with and without external perturbations. The existing models in the human control literature, including maximum smoothness, optimal feedback control with minimum effort, and dynamic primitives with impedance were revisited for this challenging task. As these control models were primarily developed for unconstrained reaching movements, they could replicate human trajectories when transporting a rigid object. However, they fell short when the object introduced complex interaction forces due to its internal dynamics. Therefore, this study extended the framework of dynamic primitives and used an optimal controller to generate a maximally smooth zero-force trajectory for the impedance operator when interacting with perturbations from the object or the environment. Given the challenges that robot control still faces when interacting with complex objects, these findings may inform the development of bio-inspired controllers for robotic manipulation.
AB - Modern computer algorithms easily beat world champions in chess or Go, but state-of-the-art robots are still outperformed by two-year-old's in manipulating the pieces, let alone interacting with more complex objects. This work studied human behavior when moving an underactuated object, a cup with a ball rolling inside creating internal dynamics like sloshing coffee in a cup. The objective was to develop a control model that could replicate human behavior. Human movement data were collected for transporting this cup-and-ball system, both with and without external perturbations. The existing models in the human control literature, including maximum smoothness, optimal feedback control with minimum effort, and dynamic primitives with impedance were revisited for this challenging task. As these control models were primarily developed for unconstrained reaching movements, they could replicate human trajectories when transporting a rigid object. However, they fell short when the object introduced complex interaction forces due to its internal dynamics. Therefore, this study extended the framework of dynamic primitives and used an optimal controller to generate a maximally smooth zero-force trajectory for the impedance operator when interacting with perturbations from the object or the environment. Given the challenges that robot control still faces when interacting with complex objects, these findings may inform the development of bio-inspired controllers for robotic manipulation.
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U2 - 10.1109/ICRA48506.2021.9561352
DO - 10.1109/ICRA48506.2021.9561352
M3 - Conference contribution
AN - SCOPUS:85124357929
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 7555
EP - 7562
BT - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Y2 - 30 May 2021 through 5 June 2021
ER -