TY - GEN
T1 - Heuristic tentacle algorithm for local path planning based on obstacles clustering concept
AU - Liu, Fangxu
AU - Li, Weiming
AU - Li, Xueyuan
AU - Bai, Tianyi
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/17
Y1 - 2020/11/17
N2 - This paper introduces a heuristic tentacle algorithm for local path planning of unmanned skid-steering vehicle. Mobility, safety and economy are three mainly focused aspects in the navigation of unmanned ground vehicles. Critical skidding and slipping often occur during the turning motion, which effect the vehicle's motion apparently. So vehicle kinematics are discussed and applied to construct the cluster of tentacles. Several path assessment criteria named obstacle avoidance, terrain roughness and distance to the global path are discussed. Based on the multi-density clustering processed in the global path planning, heuristic method is introduced to guide to search in sparse region. The simulation analysis shows the generated local path can avoid the obstacles along the global path. Simultaneously. the global path can be smoothed through kinematic aware tentacle algorithm.
AB - This paper introduces a heuristic tentacle algorithm for local path planning of unmanned skid-steering vehicle. Mobility, safety and economy are three mainly focused aspects in the navigation of unmanned ground vehicles. Critical skidding and slipping often occur during the turning motion, which effect the vehicle's motion apparently. So vehicle kinematics are discussed and applied to construct the cluster of tentacles. Several path assessment criteria named obstacle avoidance, terrain roughness and distance to the global path are discussed. Based on the multi-density clustering processed in the global path planning, heuristic method is introduced to guide to search in sparse region. The simulation analysis shows the generated local path can avoid the obstacles along the global path. Simultaneously. the global path can be smoothed through kinematic aware tentacle algorithm.
KW - Kinematics
KW - Local Path Planning
KW - Tentacle Algorithm
KW - Unmanned Skid-steered Vehicle
UR - http://www.scopus.com/inward/record.url?scp=85123040765&partnerID=8YFLogxK
U2 - 10.1145/3440084.3441189
DO - 10.1145/3440084.3441189
M3 - Conference contribution
AN - SCOPUS:85123040765
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 2020 4th International Symposium on Computer Science and Intelligent Control, ISCSIC 2020
PB - Association for Computing Machinery
T2 - 4th International Symposium on Computer Science and Intelligent Control, ISCSIC 2020
Y2 - 17 November 2020 through 19 November 2020
ER -