The Use of Gaze-Derived Confidence of Inferred Operator Intent in Adjusting Safety-Conscious Haptic Assistance
By: Jeremy D. Webb , Michael Bowman , Songpo Li and more
Potential Business Impact:
Helps robots understand what you want them to do.
Humans directly completing tasks in dangerous or hazardous conditions is not always possible where these tasks are increasingly be performed remotely by teleoperated robots. However, teleoperation is difficult since the operator feels a disconnect with the robot caused by missing feedback from several senses, including touch, and the lack of depth in the video feedback presented to the operator. To overcome this problem, the proposed system actively infers the operator's intent and provides assistance based on the predicted intent. Furthermore, a novel method of calculating confidence in the inferred intent modifies the human-in-the-loop control. The operator's gaze is employed to intuitively indicate the target before the manipulation with the robot begins. A potential field method is used to provide a guiding force towards the intended target, and a safety boundary reduces risk of damage. Modifying these assistances based on the confidence level in the operator's intent makes the control more natural, and gives the robot an intuitive understanding of its human master. Initial validation results show the ability of the system to improve accuracy, execution time, and reduce operator error.
Similar Papers
Confidence-based Intent Prediction for Teleoperation in Bimanual Robotic Suturing
Robotics
Helps surgeons perform better with robot help.
Enhancing Joint Human-AI Inference in Robot Missions: A Confidence-Based Approach
Human-Computer Interaction
Helps robots and people work better together.
A Generative System for Robot-to-Human Handovers: from Intent Inference to Spatial Configuration Imagery
Robotics
Robots learn to hand things to people smoothly.