Abstract
In this work, we present a novel vision-based solution for operating a vehicle under Gaussian Distribution Temporal Logic (GDTL) constraints without global positioning infrastructure. We first present the mapping component that builds a high-resolution map of the environment by flying a team of two aerial vehicles in formation with sensor information provided by their onboard cameras. The control policy for the ground robot is synthesized under temporal and uncertainty constraints given the semantically labeled map. Finally, the ground robot executes the control policy given pose estimates from a dedicated aerial robot that tracks and localizes the ground robot. The proposed method is validated using a two-wheeled ground robot and a quadrotor with a camera for ten successful experimental trials.
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.