This paper assesses the energy efficiency of a redundant actuation architecture combining Quasi-Direct Drive (QDD) motors and Series Elastic Actuators (SEAs) by comparing its energy consumption to Geared Motors (GMs) and SEAs alone. We consider this comparison for two robotic systems performing different tasks. Our results show that using the redundant actuation we can save up to 99% of energy with respect to SEA for sinusoidal movements. This efficiency is achieved by exploiting the coupled dynamics of the two actuators, resulting in a latching-like control strategy. We also show that these large energy savings are not straightforwardly extendable to nonsinusoidal movements, but smaller savings (e.g., 7%) are nonetheless possible. The presented results were obtained thanks to the framework of concurrent design (co-design), namely the simultaneous optimization of hardware parameters and control trajectories. This shows that the combination of complex hardware morphologies and advanced numerical co-design can lead to peak hardware performance that would be unattainable by human intuition alone.

Exploring the Limits of a Redundant Actuation System through Co-Design

Fontana M.;
2021-01-01

Abstract

This paper assesses the energy efficiency of a redundant actuation architecture combining Quasi-Direct Drive (QDD) motors and Series Elastic Actuators (SEAs) by comparing its energy consumption to Geared Motors (GMs) and SEAs alone. We consider this comparison for two robotic systems performing different tasks. Our results show that using the redundant actuation we can save up to 99% of energy with respect to SEA for sinusoidal movements. This efficiency is achieved by exploiting the coupled dynamics of the two actuators, resulting in a latching-like control strategy. We also show that these large energy savings are not straightforwardly extendable to nonsinusoidal movements, but smaller savings (e.g., 7%) are nonetheless possible. The presented results were obtained thanks to the framework of concurrent design (co-design), namely the simultaneous optimization of hardware parameters and control trajectories. This shows that the combination of complex hardware morphologies and advanced numerical co-design can lead to peak hardware performance that would be unattainable by human intuition alone.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/540431
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