2021 IEEE RAS Winter School on Simultaneous Localization and Mapping in Deformable Environments [Education]

Shoudong Huang, Liang Zhao

Research output: Contribution to journalArticlepeer-review

Abstract

Simultaneous localization and mapping (SLAM) is an important research problem for robot navigation in unknown environments, particularly when GPS is not available. SLAM requires a robot to be able to build a map of the environment in real time and simultaneously estimate its own location within the map. In the past two decades, significant progress has been made in the research for SLAM in static environments. However, when an environment has deformations, such as when a surgical robot is navigating in internal body environments, SLAM needs to build a time-varying 3D map of the soft tissues and estimate the location of the robot/sensor within the map. This poses a challenging problem since the robot/sensor is moving while the environment is deforming.
Original languageEnglish
Pages (from-to)120-122
Number of pages3
JournalIEEE Robotics and Automation Magazine
Volume29
Issue number1
DOIs
Publication statusPublished - 22 Mar 2022

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