A Blended Human-Robot Shared Control Framework to Handle Drift and Latency

Abstract In this paper, we aim to develop a shared control framework wherein the control authority is dynamically allocated between the human operator and the automation system. To this end, we have defined a shared control paradigm wherein the blending mechanism uses the confidence between a human and co-robot to allocate the control authority. To capture the confidence between the human and robot, qualitatively, a simple-but-generic model is presented wherein the confidence of human-to-robot and robot-to-human is a function of the human’s performance and robot’s performance. The computed confidence will then be used to adjust the level of autonomy between the two agents dynamically. To validate our novel framework, we propose case studies in which the steering control of a semi-automated system is shared between the human and onboard automation systems. The numerical simulations demonstrate the effectiveness of the proposed shared control paradigms.

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Modelling Non Cooperative Human-Automation Interactions in a Haptic Shared Control Framework

10.4271/2019-01-0938 ◽

2019 ◽

Cited By ~ 1

Author(s):

Amirhossein Ghasemi ◽

Arjun Yeravdekar

Keyword(s):

Shared Control ◽

Control Framework

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A Shared Control Framework for Human-Multirobot Foraging With Brain-Computer Interface

IEEE Robotics and Automation Letters ◽

10.1109/lra.2021.3092290 ◽

2021 ◽

Vol 6 (4) ◽

pp. 6305-6312

Author(s):

Wei Dai ◽

Yaru Liu ◽

Huimin Lu ◽

Zhiqiang Zheng ◽

Zongtan Zhou

Keyword(s):

Brain Computer Interface ◽

Shared Control ◽

Computer Interface ◽

Control Framework

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Game Theoretic Modeling of a Steering Operation in a Haptic Shared Control Framework

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems ◽

10.1115/dscc2018-9105 ◽

2018 ◽

Cited By ~ 2

Author(s):

Amir H. Ghasemi

Keyword(s):

Path Following ◽

Open Loop ◽

Shared Control ◽

Automation System ◽

Steering Control ◽

Human Driver ◽

Control Framework ◽

Game Theoretic ◽

Control Authority ◽

Vehicle Trajectory

Haptic shared control is expected to achieve a smooth collaboration between humans and automated systems, because haptics facilitate mutual communication. This paper addresses a the interaction between the human driver and automation system in a haptic shared control framework using a non-cooperative model predictive game approach. In particular, we focused on a scenario in which both human and automation system detect an obstacle but select different paths for avoiding it. For such a scenario, the open-loop Nash steering control solution is derived and the influence of the human driver’s impedance and path following weights on the vehicle trajectory are investigated. It is shown that by modulating the impedance and the path following weight the control authority can be shifted between the human driver and the automation system.

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