TY - GEN
T1 - Large-scale cooperative 3D visual-inertial mapping in a Manhattan world
AU - Guo, Chao X.
AU - Sartipi, Kourosh
AU - Dutoit, Ryan C.
AU - Georgiou, Georgios A.
AU - Li, Ruipeng
AU - O'Leary, John
AU - Nerurkar, Esha D.
AU - Hesch, Joel A.
AU - Roumeliotis, Stergios I.
PY - 2016/6/8
Y1 - 2016/6/8
N2 - In this paper, we address the problem of cooperative mapping (CM) using datasets collected by multiple users at different times, when the transformation between the users' starting poses is unknown. Specifically, we formulate CM as a constrained optimization problem, where each user's independently estimated trajectory and map are combined in a single map by imposing geometric constraints between commonly-observed point and line features. Furthermore, our formulation allows for modularity since new/old maps (or parts of them) can be easily added/removed with no impact on the remaining ones. Additionally, the proposed CM algorithm lends itself, for the most part, to parallel implementations, hence gaining in speed. Experimental results based on visual and inertial measurements collected from four users within two large buildings are used to assess the performance of the proposed CM algorithm.
AB - In this paper, we address the problem of cooperative mapping (CM) using datasets collected by multiple users at different times, when the transformation between the users' starting poses is unknown. Specifically, we formulate CM as a constrained optimization problem, where each user's independently estimated trajectory and map are combined in a single map by imposing geometric constraints between commonly-observed point and line features. Furthermore, our formulation allows for modularity since new/old maps (or parts of them) can be easily added/removed with no impact on the remaining ones. Additionally, the proposed CM algorithm lends itself, for the most part, to parallel implementations, hence gaining in speed. Experimental results based on visual and inertial measurements collected from four users within two large buildings are used to assess the performance of the proposed CM algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84977587468&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977587468&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2016.7487238
DO - 10.1109/ICRA.2016.7487238
M3 - Conference contribution
AN - SCOPUS:84977587468
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 1071
EP - 1078
BT - 2016 IEEE International Conference on Robotics and Automation, ICRA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Robotics and Automation, ICRA 2016
Y2 - 16 May 2016 through 21 May 2016
ER -