TY - JOUR
T1 - 2021 IEEE RAS Winter School on Simultaneous Localization and Mapping in Deformable Environments [Education]
AU - Huang, Shoudong
AU - Zhao, Liang
PY - 2022/3/22
Y1 - 2022/3/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85127610085&partnerID=8YFLogxK
U2 - 10.1109/MRA.2022.3145919
DO - 10.1109/MRA.2022.3145919
M3 - Article
AN - SCOPUS:85127610085
SN - 1070-9932
VL - 29
SP - 120
EP - 122
JO - IEEE Robotics and Automation Magazine
JF - IEEE Robotics and Automation Magazine
IS - 1
ER -