@inproceedings{7e4a8795b040404882d855865ea6adb5,
title = "Efficient active SLAM based on submap joining",
abstract = "This paper considers the active SLAM problem where a robot is required to cover a given area while at the same time performing simultaneous localization and mapping (SLAM) for understanding the environment and localizing the robot itself. We propose a model predictive control (MPC) framework, and the minimization of uncertainty in SLAM and coverage problems are solved respectively by the Sequential Quadratic Programming (SQP) method. Then, a decision making process is used to control the switching of two control inputs. In order to reduce the estimation and planning time, we use Linear SLAM, which is a submap joining approach. Simulation results are presented to validate the effectiveness of the proposed active SLAM strategy.",
author = "Yongbo Chen and Shoudong Huang and Robert Fitch and Jianqiao Yu",
year = "2017",
language = "English",
series = "Australasian Conference on Robotics and Automation, ACRA",
publisher = "Australasian Robotics and Automation Association",
pages = "141--147",
editor = "Alen Alempijevic and Calleja, \{Teresa Vidal\} and Sarath Kodagoda",
booktitle = "Australasian Conference on Robotics and Automation, ACRA 2017",
address = "Australia",
note = "Australasian Conference on Robotics and Automation, ACRA 2017 ; Conference date: 11-12-2017 Through 13-12-2017",
}