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

Grandesso, Gianluigi; Wensing, Patrick M.; Fontana, Marco; Prete, Andrea Del

doi:10.1109/access.2021.3072783

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…Moreover, besides using CACTO as initial guess provider for TO, where the RL and TO environments must match, we are interested in using it as a deep RL technique to find directly a control policy, where the two environments do not need to match (e.g., the TO problem could be a simplified version of the RL environment without noise sources). Finally, we plan to extend CACTO to optimize also hardware parameters, to create a concurrent design (co-design) framework robust against the local minima problem, which is a crucial issue in co-design applications [35].…”

Section: Discussionmentioning

confidence: 99%

CACTO: Continuous Actor-Critic With Trajectory Optimization—Towards Global Optimality

Grandesso

Alboni

Papini

et al. 2023

IEEE Robot. Autom. Lett.

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This paper presents a novel algorithm for the continuous control of dynamical systems that combines Trajectory Optimization (TO) and Reinforcement Learning (RL) in a single framework. The motivations behind this algorithm are the two main limitations of TO and RL when applied to continuous nonlinear systems to minimize a non-convex cost function. Specifically, TO can get stuck in poor local minima when the search is not initialized close to a "good" minimum. On the other hand, when dealing with continuous state and control spaces, the RL training process may be excessively long and strongly dependent on the exploration strategy. Thus, our algorithm learns a "good" control policy via TO-guided RL policy search that, when used as initial guess provider for TO, makes the trajectory optimization process less prone to converge to poor local optima. Our method is validated on several reaching problems featuring non-convex obstacle avoidance with different dynamical systems, including a car model with 6D state, and a 3-joint planar manipulator. Our results show the great capabilities of CACTO in escaping local minima, while being more computationally efficient than the Deep Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization (PPO) RL algorithms.

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Section: Discussionmentioning

confidence: 99%

CACTO: Continuous Actor-Critic With Trajectory Optimization—Towards Global Optimality

Grandesso

Alboni

Papini

et al. 2023

IEEE Robot. Autom. Lett.

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“…However, this results in a heavy actuation system and low overall efficiency [2]. A common method to obtain a compact and relatively efficient drivetrain is by combining a smaller electric motor with a gear reduction system to reduce the motor torque requirement [3][4][5][6][7]. This is the most commonly used topology and therefore the reference topology of this study.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Drivetrain Topologies for an Ankle Gait Cycle

et al. 2022

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Powered prosthesis actuation is a field where energy efficiency and mass are important characteristics. The motion requirements of high torque at low speed and low torque at high speed are difficult to effectively combine in a single electric motor. A possibility is to use an oversized direct–drive motor that can deliver the peak torque. However, this results in a heavy actuation system and low overall efficiency. A common practice is combining a smaller electric motor with a gear reduction system. In the literature, novel redundant electric actuation systems have been presented with or without locking mechanisms to mitigate this problem. In this work, we provide a comparison of multiple electrical actuation systems composed of electric motors, gear reduction systems and locking mechanisms. This is done using the gait cycle of a human ankle as a case study. An electric motor with a double stator and a single rotor combined with a gearbox shows the most promising overall results when taking energy loss, total mass and complexity of the system into account.

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Exploring Control Co-Design's Versatility in System Optimisation: A Case Study of DC Motors

Nazaré,

Queinnec,

Nepomuceno

2024

2024 32nd Mediterranean Conference on Control and Automation (MED)

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

Abstract: This project has received funding from the Italian Ministry for Education, University, and Research (MIUR) through the "Departments of Excellence" programme.

Cited by 8 publications

References 27 publications

CACTO: Continuous Actor-Critic With Trajectory Optimization—Towards Global Optimality

CACTO: Continuous Actor-Critic With Trajectory Optimization—Towards Global Optimality

Comparison of Drivetrain Topologies for an Ankle Gait Cycle

Exploring Control Co-Design's Versatility in System Optimisation: A Case Study of DC Motors

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