Abstract
In this paper, we show that visual servoing can be formulated as an acceleration-resolved, quadratic optimization problem. This allows us to handle visual constraints, such as field of view and occlusion avoidance, as inequalities. Furthermore, it allows us to easily integrate visual servoing tasks into existing whole-body control frameworks for humanoid robots, which simplifies prioritization and requires only a posture task as a regularization term. Finally, we show this method working on simulations with HRP-4 and real tests on Romeo.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.