TY - GEN
T1 - Action Node Graph
T2 - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
AU - Umeyama, Ryusuke
AU - Niijima, Shun
AU - Sasaki, Yoko
AU - Takemura, Hiroshi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper proposes a graph design for the action planning of autonomous mobile robots in cities. When moving in city environments, not only movements but also various other actions such as opening a door or crossing the street need to be considered. Autonomous robots are required to plan their routes while balancing the cost of both movements and required actions. To enable this, we developed the "action node graph, "a graphical representation of a robot's mobility environment. Autonomous robots can use this action node graph to obtain the optimal route to the destination and determine the required actions according to their specifications. An action node graph can be easily constructed from geospatial information and is automatically converted into a behavior tree to be used for the autonomous navigation of a variety of mobile robots. We used a wheeled robot to demonstrate autonomous navigation around crossings and buildings.
AB - This paper proposes a graph design for the action planning of autonomous mobile robots in cities. When moving in city environments, not only movements but also various other actions such as opening a door or crossing the street need to be considered. Autonomous robots are required to plan their routes while balancing the cost of both movements and required actions. To enable this, we developed the "action node graph, "a graphical representation of a robot's mobility environment. Autonomous robots can use this action node graph to obtain the optimal route to the destination and determine the required actions according to their specifications. An action node graph can be easily constructed from geospatial information and is automatically converted into a behavior tree to be used for the autonomous navigation of a variety of mobile robots. We used a wheeled robot to demonstrate autonomous navigation around crossings and buildings.
UR - http://www.scopus.com/inward/record.url?scp=85126221913&partnerID=8YFLogxK
U2 - 10.1109/SII52469.2022.9708779
DO - 10.1109/SII52469.2022.9708779
M3 - Conference contribution
AN - SCOPUS:85126221913
T3 - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
SP - 645
EP - 651
BT - 2022 IEEE/SICE International Symposium on System Integration, SII 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 January 2022 through 12 January 2022
ER -