Toward Safe Human–Robot Interaction: A Fast- Response Admittance Control Method for Series Elastic Actuator

Zhong, Haoran; Li, Xinyu; Gao, Liang; Li, Congbo

doi:10.1109/tase.2021.3057883

Cited by 11 publications

(8 citation statements)

References 57 publications

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“…A flexible Bowden cable that passed through the rod connected the output shaft of the motor with the load cell which was fixed to a leaf spring. The customized leaf spring increased structure passive compliance, thus improving comfortability and safety of human-exoskeleton interaction (Zhong et al, 2021 ). The foot frame connected the exoskeleton joint shaft with the forefoot plate which was fixed under the exoskeleton shoe to ensure synchronous movement of the exoskeleton and human ankle.…”

Section: Methodsmentioning

confidence: 99%

Improving Walking Economy With an Ankle Exoskeleton Prior to Human-in-the-Loop Optimization

et al. 2022

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Lower limb robotic exoskeletons have shown the capability to enhance human locomotion for healthy individuals or to assist motion rehabilitation and daily activities for patients. Recent advances in human-in-the-loop optimization that allowed for assistance customization have demonstrated great potential for performance improvement of exoskeletons. In the optimization process, subjects need to experience multiple types of assistance patterns, thus, leading to a long evaluation time. Besides, some patterns may be uncomfortable for the wearers, thereby resulting in unpleasant optimization experiences and inaccurate outcomes. In this study, we investigated the effectiveness of a series of ankle exoskeleton assistance patterns on improving walking economy prior to optimization. We conducted experiments to systematically evaluate the wearers' biomechanical and physiological responses to different assistance patterns on a lightweight cable-driven ankle exoskeleton during walking. We designed nine patterns in the optimization parameters range which varied peak torque magnitude and peak torque timing independently. Results showed that metabolic cost of walking was reduced by 17.1 ± 7.6% under one assistance pattern. Meanwhile, soleus (SOL) muscle activity was reduced by 40.9 ± 19.8% with that pattern. Exoskeleton assistance changed maximum ankle dorsiflexion and plantarflexion angle and reduced biological ankle moment. Assistance pattern with 48% peak torque timing and 0.75 N·m·kg−1 peak torque magnitude was effective in improving walking economy and can be selected as an initial pattern in the optimization procedure. Our results provided a preliminary understanding of how humans respond to different assistances and can be used to guide the initial assistance pattern selection in the optimization.

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Section: Methodsmentioning

confidence: 99%

Improving Walking Economy With an Ankle Exoskeleton Prior to Human-in-the-Loop Optimization

et al. 2022

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“…quantitatively measure the effect of this change. Our experimental environment was based on the Multi-Agent Particle Environment [24], [25], a simple multi-agent particle world based on some basic simulated physics. The environment was modified to include more objects and improve rendering.…”

Section: A Experiments Settingmentioning

confidence: 99%

Collective Conditioned Reflex: A Bio-Inspired Fast Emergency Reaction Mechanism for Designing Safe Multi-Robot Systems

He¹,

Zhao²,

Luo³

et al. 2022

Preprint

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A multi-robot system (MRS) is a group of coordinated robots designed to cooperate with each other and accomplish set tasks. Due to the uncertainties in operating environments, the system may encounter unexpected emergencies, such as unobserved obstacles, unexpectedly moving vehicles, explosions, and fires. Animal groups such as bee colonies initiate collective emergency reaction behaviors such as bypassing the front trees and avoiding back predators, similar to muscle conditioned reflex which organizes local muscles to avoid hazards in the first response without delaying passage through the central brain. Inspired by this, we develop a similar collective conditioned reflex mechanism for multi-robot systems to respond to emergencies. In this study, Collective Conditioned Reflex (CCR), a bio-inspired emergency reaction mechanism, is developed based on animal collective behavior analysis and multi-agent reinforcement learning. The algorithm uses a physical model to determine if the robots are experiencing an emergency; then, rewards for robots involved in the emergency are augmented with corresponding heuristic rewards, which evaluate emergency magnitudes and consequences and decide local robots' participation. CCR is validated on three typical emergency scenarios: unexpected turbulence, strong wind, and uncertain obstacle. Experimental results demonstrate that CCR improves robot teams' emergency reaction capability with faster reaction speed and safer trajectory adjustment compared with traditional methods.

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“…As G uniquely consists of two primary terms I and C, and the effect of I and C on Q and E of H to create HA-terms are similar, the fuzziness of the primary terms and hedges are measured through Equation (7) to Equation ( 14) as:…”

Section: Ha-based Admittance Controller With Four Point Bilinear Inte...mentioning

confidence: 99%

“…Moreover, the natural human-robot interaction is rarely of concern, yet it is crucial to obtain effective cooperation. These shortcomings can be found in previous studies on pHRI, such as [1][2][3][4][5][6][7], and are presented clearly in [8][9][10]. By contrast, the natural human-robot cooperation is considered elaborately for non-physical interactions, as presented in [11,12].…”

Section: Introductionmentioning

confidence: 96%

A MLP-Hedge-Algebras Admittance Controller for Physical Human–Robot Interaction

Toan

Khôi

2021

Applied Sciences

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Recently, the identification of inertia and damping matrices (IIDM) and safety issues, as well as natural cooperation, are interestingly considered to enhance the quality of the physical human–robot interaction (pHRI). To cover all of these issues, advanced admittance controllers, such as those based on fuzzy logic or hedge algebras, have been formulated and successfully applied in several industrial problems. However, the inference mechanism of those kinds of controllers causes the discreteness of the super surface describing the input–output relationship in the Cartesian coordinates. As a consequence, the quality of the safe-natural cooperation between humans and robots is negatively affected. This paper presents an alternative admittance controller for pHRI by using a combination of hedge algebras and multilayer perceptron neural network (MLP), whose purpose is to create a more accurate inference mechanism for the admittance controller. To our best knowledge, this is the first time that such a neural network is considered for the inference mechanism of hedge algebras and also the first time that such an admittance controller is used for pHRI. The proposed admittance controller is verified on a teaching task using a 6-DOF manipulator. Experimental results have shown that the proposed method provides better cooperation compared with previous methods.

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Toward Safe Human–Robot Interaction: A Fast- Response Admittance Control Method for Series Elastic Actuator

Cited by 11 publications

References 57 publications

Improving Walking Economy With an Ankle Exoskeleton Prior to Human-in-the-Loop Optimization

Improving Walking Economy With an Ankle Exoskeleton Prior to Human-in-the-Loop Optimization

Collective Conditioned Reflex: A Bio-Inspired Fast Emergency Reaction Mechanism for Designing Safe Multi-Robot Systems

A MLP-Hedge-Algebras Admittance Controller for Physical Human–Robot Interaction

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