Addressing agent disagreement in mixed-initiative traded control for confined-space manufacturing

Owan, Parker; Garbini, Joseph L.; Devasia, Santosh

doi:10.1109/aim.2017.8014022

“…They solve authority conflicts by reallocating these resources based on task-specific predefined authority priorities. Owan et al [8] propose a consensus procedure based on heuristically determined timeout thresholds to solve control conflicts. When consent cannot be reached, similarly to [9], a task-specific heuristic contingency procedure is triggered based on predefined authority priorities.…”

Section: Related Workmentioning

confidence: 99%

“…We advance existing coordination strategies from related work (cf. [1], [6], [8], [9]) to solve the conflict for control explicitly through a negotiation framework without the need for context awareness or identifying human intent. The contribution of the paper is threefold: a) a negotiation theoretic framework is proposed that enables both agents, i. e. the robot's AI and the human operator, to initiate a negotiation in any given situation and to ultimately cooperatively decide on whether or not to switch the LOA; b) an implementation of the negotiation framework integrated with an advanced MI control method from related work; c) an experimental study evaluating the proposed method and comparing it to previous MI control.…”

Section: Introductionmentioning

confidence: 99%

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

Rothfuß¹,

Chiou²,

Inga³

et al. 2022

Preprint

2

0

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This paper is accepted for the IEEE SMC 2022 conference and addresses the problem of transfer of control authority between a robot’s AI and a remote human operator, when controlling a Mixed-Initiative (MI) robotic system. We propose a negotiation-theoretic method that enables the robot’s AI and the human operator to cooperatively and dynamically determine (i. e. negotiate) the transfer of control authority between these two agents. An experimental study is presented in which a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) method is compared with our proposed Negotiation-Enabled Mixed-Initiative Control Switcher (NEMICS) algorithm. Results suggest that the NEMICS framework is able to successfully avoid conflicts for control, which is a fundamental challenge encountered with previous MI control methods. Comparing NEMICS with the EMICS, we provide evidence of improved navigational safety (i. e. fewer collisions). Additionally, our usability study suggests that human operators perceived their interactions with NEMICS as less intrusive than with EMICS. The accompanying video demonstrates the differences between NEMICS and EMICS.

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“…Most relevant to our work is the papers of Mercier et al [9] and Owan et al [8]. Mercier et al [9] propose an authority dynamics controller based on a dependence graph of resources, such as the robot's wheels or its pose.…”

Section: Related Workmentioning

confidence: 99%

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

Rothfuß¹,

Chiou²,

Inga³

et al. 2022

Preprint

2

0

View full text Add to dashboard Cite

This paper is accepted for the IEEE SMC 2022 conference and addresses the problem of transfer of control authority between a robot’s AI and a remote human operator, when controlling a Mixed-Initiative (MI) robotic system. We propose a negotiation-theoretic method that enables the robot’s AI and the human operator to cooperatively and dynamically determine (i. e. negotiate) the transfer of control authority between these two agents. An experimental study is presented in which a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) method is compared with our proposed Negotiation-Enabled Mixed-Initiative Control Switcher (NEMICS) algorithm. Results suggest that the NEMICS framework is able to successfully avoid conflicts for control, which is a fundamental challenge encountered with previous MI control methods. Comparing NEMICS with the EMICS, we provide evidence of improved navigational safety (i. e. fewer collisions). Additionally, our usability study suggests that human operators perceived their interactions with NEMICS as less intrusive than with EMICS. The accompanying video demonstrates the differences between NEMICS and EMICS.

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“…The teleoperated control mode can combine the human's cognitive capability with the telerobot's reliability and speed. In [29], an integrated scheme of explicit consensus and consent of the agent was proposed for conflict issues between the telerobot and the human operators. The peg-in-hole task demonstrated the effectiveness of the proposed traded control strategy in a confined operation space.…”

Section: Flexible Manufacturementioning

confidence: 99%

Combined perception, control, and learning for teleoperation: key technologies, applications, and challenges

Luo

¹

,

He

²

,

Yang

³

2020

Cognitive Computation and Systems

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Teleoperation provides a promising way for human-robot collaboration in the unknown or unstructured environments to perform a cooperative task. It enables humans to complete a task at a remote side and combines both the human's intelligence and the robots' capabilities in a collaborative task. Therefore, it is necessary to conduct cross researches in terms of robotics, artificial intelligence, sensors, and mechatronics. This study covers the state-of-the-arts research in terms of perception, control, and learning. In this review, key technologies about information perception mechanism, control algorithms, human-robot interface, and robot learning strategies for teleoperation are introduced. Then, a comprehensive survey is summarised in representative applications in teleoperation, and the existing challenges and potential directions of the development are discussed.

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Addressing agent disagreement in mixed-initiative traded control for confined-space manufacturing

Cited by 9 publications

References 9 publications

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

Combined perception, control, and learning for teleoperation: key technologies, applications, and challenges

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