A collaborative visual localization scheme for a low-cost heterogeneous robotic team with non-overlapping perspectives

Benjamin Abruzzo, David Cappelleri, Philippos Mordohai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents and evaluates a relative localization scheme for a heterogeneous team of low-cost mobile robots. An error-state, complementary Kalman Filter was developed to fuse analytically-derived uncertainty of stereoscopic pose measurements of an aerial robot, made by a ground robot, with the inertial/visual proprioceptive measurements of both robots. Results show that the sources of error, image quantization, asynchronous sensors, and a non-stationary bias, were sufficiently modeled to estimate the pose of the aerial robot. In both simulation and experiments, we demonstrate the proposed methodology with a heterogeneous robot team, consisting of a UAV and a UGV tasked with collaboratively localizing themselves while avoiding obstacles in an unknown environment. The team is able to identify a goal location and obstacles in the environment and plan a path for the UGV to the goal location. The results demonstrate localization accuracies of 2cm to 4cm, on average, while the robots operate at a distance from each-other between 1m and 4m.

Original languageEnglish
Title of host publication43rd Mechanisms and Robotics Conference
ISBN (Electronic)9780791859230
DOIs
StatePublished - 2019
EventASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2019 - Anaheim, United States
Duration: 18 Aug 201921 Aug 2019

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume5A-2019

Conference

ConferenceASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2019
Country/TerritoryUnited States
CityAnaheim
Period18/08/1921/08/19

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