Year: 2023
Type: conference-paper
Abstract: Many solutions tailored for intuitive visualization or teleoperation of virtual, augmented and mixed (VAM) reality systems are not robust to robot failures, such as the inability to detect and recognize objects in the environment or planning unsafe trajectories. In this paper, we present a novel virtual reality (VR) framework where users can (i) recognize when the robot has failed to detect a real- world object, (ii) correct the error in VR, (iii) modify proposed object trajectories and, (iv) implement behaviors on a real-world robot. Finally, we propose a user study aimed at testing the efficacy of our framework. Project materials can be found in the OSF repository.
Institution: KTH Royal Institute of Technology
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4320187626