Modulating Human Input for Shared Autonomy in Dynamic Environments

Christopher E. Mower, João Moura, Aled Davies, Sethu Vijayakumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Many robotic tasks require human interaction through teleoperation to achieve high performance. However, in industrial applications these methods often require high levels of concentration and manual dexterity leading to high cognitive loads and dangerous working conditions. Shared autonomy attempts to address these issues by blending human and autonomous reasoning, relieving the burden of precise motor control, tracking, and localization. In this paper we propose an optimization-based representation for shared autonomy in dynamic environments. We ensure real-time tractability by modulating the human input with the information of the changing environment in the same task space, instead of adding it to the optimization cost or constraints. We illustrate the method with two real world applications: grasping objects in a cluttered environment, and a spraying task requiring sprayed linings with greater homogeneity. Finally we use a 7 degree of freedom KUKA LWR arm to simulate the grasping and spraying experiments.
Original languageEnglish
Title of host publication2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)978-1-7281-2622-7
ISBN (Print)978-1-7281-2623-4
Publication statusPublished - 13 Jan 2020
Event28th IEEE International Conference on Robot & Human Interactive Communication - New Delhi, India
Duration: 14 Oct 201918 Oct 2019

Publication series

ISSN (Print)1944-9445
ISSN (Electronic)1944-9437


Conference28th IEEE International Conference on Robot & Human Interactive Communication
Abbreviated titleRo-Man 2019
CityNew Delhi
Internet address


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