scholarly journals Energy-shaping control of soft continuum manipulators with in-plane disturbances

2020 ◽  
pp. 027836492090767
Author(s):  
Enrico Franco ◽  
Arnau Garriga-Casanovas
Keyword(s):  
Adaptive Estimation ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Energy Shaping ◽  
Practical Applications ◽  
Medical Interventions ◽  
Continuum Manipulators ◽  
Unknown Disturbances ◽  
Single Input ◽  
Constant Section

Soft continuum manipulators offer levels of compliance and inherent safety that can render them a superior alternative to conventional rigid robots for a variety of tasks, such as medical interventions or human–robot interaction. However, the ability of soft continuum manipulators to compensate for external disturbances needs to be further enhanced to meet the stringent requirements of many practical applications. In this paper, we investigate the control problem for soft continuum manipulators that consist of one inextensible segment of constant section, which bends under the effect of the internal pressure and is subject to unknown disturbances acting in the plane of bending. A rigid-link model of the manipulator with a single input pressure is employed for control purposes and an energy-shaping approach is proposed to derive the control law. A method for the adaptive estimation of disturbances is detailed and a disturbance compensation strategy is proposed. Finally, the effectiveness of the controller is demonstrated with simulations and with experiments on an inextensible soft continuum manipulator that employs pneumatic actuation.

scholarly journals A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yiming Jiang ◽  
Chenguang Yang ◽  
Jing Na ◽  
Guang Li ◽  
Yanan Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Nonlinear Systems ◽  
Human Robot Interaction ◽  
Learning Tools ◽  
Robot Interaction ◽  
Practical Applications ◽  
Powerful Learning ◽  
Wide Range ◽  
Complex Nonlinear Systems ◽  
And Control

As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.

scholarly journals Single-input adaptive fuzzy sliding mode control of the lower extremity exoskeleton based on human–robot interaction

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401668666 ◽  
Author(s):  
Xinglai Jin ◽  
Shiqiang Zhu ◽  
Xiaocong Zhu ◽  
Qingcheng Chen ◽  
Xuequn Zhang
Keyword(s):  
Lower Extremity ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Human Robot Interaction ◽  
Tracking Performance ◽  
Robot Interaction ◽  
Fuzzy Sliding Mode Control ◽  
Adaptive Fuzzy Sliding Mode ◽  
Fuzzy Sliding Mode ◽  
Single Input

This article introduces a human–robot interaction controller toward the lower extremity exoskeleton whose aim is to improve the tracking performance and drive the exoskeleton to shadow the wearer with less interaction force. To acquire the motion intention of the wearer, two subsystems are designed: the first is to infer the wearer is in which phase based on floor reaction force detected by a multi-sensor system installed in the sole, and the second is to infer the motion velocity based on the multi-axis force sensor and admittance model. An improved single-input fuzzy sliding mode controller is designed, and the adaptive switching controller is combined to promote the tracking performance considering system uncertainties. Adaptation laws are designed based on the Lyapunov stability theorem. Therefore, the stability of the single-input adaptive fuzzy sliding mode control can be guaranteed. Finally, the proposed methods are applied to the lower extremity exoskeleton, especially in the swing phase. Its effectiveness is validated by comparative experiments.

scholarly journals Feedback linearization for decoupled position/stiffness control of bidirectional antagonistic drives

2018 ◽  
Vol 31 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Kosta Jovanovic ◽  
Branko Lukic ◽  
Veljko Potkonjak
Keyword(s):  
Feedback Linearization ◽  
Robot Control ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Interaction Impedance ◽  
Single Input Single Output ◽  
Mechanical Structure ◽  
Single Output ◽  
Single Input ◽  
Stiffness Control

To ensure safe human-robot interaction impedance robot control has arisen as one of the key challenges in robotics. This paper elaborates control of bidirectional antagonistic drives - qbmove maker pro. Due to its mechanical structure, both position and stiffness of bidirectional antagonistic drives could be controlled independently. To that end, we applied feedback linearization. Feedback linearization based approach initially decouples systems in two linear single-input-single-output subsystems: position subsystem and stiffness subsystem. The paper elaborates preconditions for feedback linearization and its implementation. The paper presents simulation results that prove the concept but points out application issues due to the complex mechanical structure of the bidirectional antagonistic drives.

Workload in Human-Robot Interaction: A Review of Manipulations and Outcomes

2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

Biomimetic, sociable robots for human-robot interaction

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

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