TY - GEN
T1 - A study on path planning for small mobile robot to move in forest area
AU - Tanaka, K.
AU - Okamoto, Y.
AU - Ishii, H.
AU - Kuroiwa, D.
AU - Yokoyama, H.
AU - Inoue, S.
AU - Shi, Q.
AU - Okabayashi, S.
AU - Sugahara, Y.
AU - Takanishi, A.
N1 - Funding Information:
ACKNOWLEDGMENT This study was conducted at the Waseda Research Institute for Science and Engineering, the Humanoid Robotics Institute, and the Future Robotics Organization, Waseda University. This research is supported by the Consolidated Research Institute for Advanced Science and Medical Care, Waseda University (ASMeW), SolidWorks K.K., Leading Graduate Program in Science and Engineering, Waseda University from MEXT, Japan, and Grant-in-Aid for JSPS Research Fellow.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/3/23
Y1 - 2018/3/23
N2 - We are developing an autonomous monitoring system using mobile robot in response to the demands of autonomous monitoring in forest area. The effective path planning is required for autonomous operation. The robot needs to locomote in the grassy area so as to move in a natural forest area, therefore the path route on grassy area have to be considered. The objective of this study was to develop a path planning method for small mobile robot to move in the forest. We focused on the cost used to generate the path and try to add grass vegetation into the cost map. The grass vegetation degree is effective to generate the optimal path, and the robot could move in forest by following the generated path.
AB - We are developing an autonomous monitoring system using mobile robot in response to the demands of autonomous monitoring in forest area. The effective path planning is required for autonomous operation. The robot needs to locomote in the grassy area so as to move in a natural forest area, therefore the path route on grassy area have to be considered. The objective of this study was to develop a path planning method for small mobile robot to move in the forest. We focused on the cost used to generate the path and try to add grass vegetation into the cost map. The grass vegetation degree is effective to generate the optimal path, and the robot could move in forest by following the generated path.
KW - Filed Robot
KW - Forestry
KW - Mobile Robot
KW - Path Planning
UR - http://www.scopus.com/inward/record.url?scp=85050026810&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050026810&partnerID=8YFLogxK
U2 - 10.1109/ROBIO.2017.8324740
DO - 10.1109/ROBIO.2017.8324740
M3 - Conference contribution
AN - SCOPUS:85050026810
T3 - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
SP - 2167
EP - 2172
BT - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Y2 - 5 December 2017 through 8 December 2017
ER -