TY - GEN
T1 - Local_INN
T2 - 2023 IEEE International Conference on Robotics and Automation, ICRA 2023
AU - Zang, Zirui
AU - Zheng, Hongrui
AU - Betz, Johannes
AU - Mangharam, Rahul
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Robot localization is an inverse problem of finding a robot's pose using a map and sensor measurements. In recent years, Invertible Neural Networks (INN s) have successfully solved ambiguous inverse problems in various fields. This paper proposes a framework that approaches the localization problem with INN. We design a network that provides implicit map representation in the forward path and localization in the inverse path. By sampling the latent space in evaluation, Local_INN outputs robot poses with covariance, which can be used to estimate the uncertainty. We show that the localization performance of Local_INN is on par with current methods with much lower latency. We show detailed 2D and 3D map reconstruction from Local_INN using poses exterior to the training set. We also provide a global localization algorithm using Local_INN to tackle the kidnapping problem.
AB - Robot localization is an inverse problem of finding a robot's pose using a map and sensor measurements. In recent years, Invertible Neural Networks (INN s) have successfully solved ambiguous inverse problems in various fields. This paper proposes a framework that approaches the localization problem with INN. We design a network that provides implicit map representation in the forward path and localization in the inverse path. By sampling the latent space in evaluation, Local_INN outputs robot poses with covariance, which can be used to estimate the uncertainty. We show that the localization performance of Local_INN is on par with current methods with much lower latency. We show detailed 2D and 3D map reconstruction from Local_INN using poses exterior to the training set. We also provide a global localization algorithm using Local_INN to tackle the kidnapping problem.
UR - http://www.scopus.com/inward/record.url?scp=85168665824&partnerID=8YFLogxK
U2 - 10.1109/ICRA48891.2023.10161015
DO - 10.1109/ICRA48891.2023.10161015
M3 - Conference contribution
AN - SCOPUS:85168665824
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 11742
EP - 11748
BT - Proceedings - ICRA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 May 2023 through 2 June 2023
ER -