Trust-based mixed-initiative teleoperation of mobile robots

Saeidi, Hamed; McLane, F.; Sadrfaidpour, B.; Sand, Evan; Fu, Sheng; Rodriguez, Jason D.; Wagner, John R.; Wang, Y.

doi:10.1109/acc.2016.7526640

Cited by 24 publications

(12 citation statements)

References 12 publications

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“…For example, researchers have developed systems that estimate the degree to which the human and robot are consistent in their actions and then updates the behavior of the robot to better align with the human [33]. Other's have described a bi-direction human-robot trust metric based on task performance [27] and even developed a taskagnostic notion of robot trust that is instead based on the user's understanding of the dynamic system [4].…”

Section: A Shared Controlmentioning

confidence: 99%

Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics

Broad¹,

Murphey

Argall³

2017

Robotics: Science and Systems XIII

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Abstract-We present a novel approach to shared control of human-machine systems. Our method assumes no a priori knowledge of the system dynamics. Instead, we learn both the dynamics and information about the user's interaction from observation through the use of the Koopman operator. Using the learned model, we define an optimization problem to compute the optimal policy for a given task, and compare the user input to the optimal input. We demonstrate the efficacy of our approach with a user study. We also analyze the individual nature of the learned models by comparing the effectiveness of our approach when the demonstration data comes from a user's own interactions, from the interactions of a group of users and from a domain expert. Positive results include statistically significant improvements on task metrics when comparing a user-only control paradigm with our shared control paradigm. Surprising results include findings that suggest that individualizing the model based on a user's own data does not effect the ability to learn a useful dynamic system. We explore this tension as it relates to developing human-in-theloop systems further in the discussion.

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Section: A Shared Controlmentioning

confidence: 99%

Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics

Broad¹,

Murphey

Argall³

2017

Robotics: Science and Systems XIII

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“…Fully distributed control algorithms are presented by Franchi et al [4], where stability is ensured in the presence of split and join events. Other interesting extensions of bilateral teleoperation are presented in [5] and [6]. Varnell and Zhang [5] employ a non-classical humanrobot interfaces, namely a tablet, and discuss the stability while assuming a human pointing model.…”

Section: Introductionmentioning

confidence: 99%

“…Varnell and Zhang [5] employ a non-classical humanrobot interfaces, namely a tablet, and discuss the stability while assuming a human pointing model. Saeidi et al [6] introduce the notion of robot-to-human trust and mixed Information flows in the intended scenario of human-robotic network system. initiative control scheme in order to improve the performance and reduce workload of the operator.…”

Section: Introductionmentioning

confidence: 99%

Passivity-based control of human-robotic networks with inter-robot communication delays and experimental verification

Yamauchi

Atman

Hatanaka

et al. 2017

2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)

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Abstract-In this paper, we present experimental studies on a cooperative control system for human-robotic networks with inter-robot communication delays. We first design a cooperative controller to be implemented on each robot so that their motion are synchronized to a reference motion desired by a human operator, and then point out that each robot motion ensures passivity. Inter-robot communication channels are then designed via so-called scattering transformation which is a technique to passify the delayed channel. The resulting robotic network is then connected with human operator based on passivity theory. In order to demonstrate the present control architecture, we build an experimental testbed consisting of multiple robots and a tablet. In particular, we analyze the effects of the communication delays on the human operator's behavior.

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“…Recently, the arbitration based on the estimation of human trust and self-confidence has been validated. In [95] a mixed-initiative bilateral teleoperation is proposed for the control of a single mobile robot. It uses trust models to scale the manual and the autonomous control inputs with a human-to-robot trust and to scale feedback with a robot-to-human trust.…”

Section: Control For the Overlapping Interactionmentioning

confidence: 99%

Control sharing in human-robot team interaction

Musić

Hirche

2017

Annual Reviews in Control

122

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The interaction between humans and robot teams is highly relevant in many application domains, for example in collaborative manufacturing, search and rescue, and logistics. It is well-known that humans and robots have complementary capabilities: Humans are excellent in reasoning and planning in unstructured environments, while robots are very good in performing tasks repetitively and precisely. In consequence, one of the key research questions is how to combine human and robot team decision making and task execution capabilities in order to exploit their complementary skills. From a controls perspective this question boils down to how control should be shared among them. This article surveys advances in humanrobot team interaction with special attention devoted to control sharing methodologies. Additionally, aspects affecting the control sharing design, such as human behavior modeling, level of autonomy and humanmachine interfaces are identified. Open problems and future research directions towards joint decision making and task execution in human-robot teams are discussed.

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Trust-based mixed-initiative teleoperation of mobile robots

Cited by 24 publications

References 12 publications

Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics

Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics

Passivity-based control of human-robotic networks with inter-robot communication delays and experimental verification

Control sharing in human-robot team interaction

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