TY - GEN
T1 - A Multi-Source Potential Field for Off-Road Path Planning
AU - Xie, Yujia
AU - Nie, Shida
AU - Liu, Hui
AU - Han, Lijin
AU - Guo, Congshuai
AU - Zhang, Fawang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Off-road environments with varied terrain and obstacle types pose challenges for safe maneuvering of unmanned ground vehicles (UGVs). In this paper, the multi-source off-road potential field (MOPF) is proposed to quantify the risk and impedimental effects on vehicle travel in off-road environments by taking the effect of the three-dimensional terrain and obstacles into account in combination with the vehicle performance and state. First, vehicle failure conditions are defined based on dynamics analysis, and crossable and non-crossable terrain are classified to consider the limitations of vehicle performance on various terrain. The non-uniform safety margin potential field (NSMPF) is proposed, based on which the non-crossable terrain source potential field (NTSPF) and the non-crossable obstacle source potential field (NOSPF) are established to quantify the risk, which can help vehicle effectively avoid unnecessary detours and save energy. The crossable obstacle source potential field (COSPF) and terrain source potential field (TSPF) are established to represent the impedimental effect of off-road environment on vehicle traveling. Finally, an application example of the MOPF in path planning is given. The MOPF has been proved by simulation to generate paths with short lengths and match the vehicle performance, while ensuring collision avoidance. In addition, the MOPF can also include different human needs and driving styles.
AB - Off-road environments with varied terrain and obstacle types pose challenges for safe maneuvering of unmanned ground vehicles (UGVs). In this paper, the multi-source off-road potential field (MOPF) is proposed to quantify the risk and impedimental effects on vehicle travel in off-road environments by taking the effect of the three-dimensional terrain and obstacles into account in combination with the vehicle performance and state. First, vehicle failure conditions are defined based on dynamics analysis, and crossable and non-crossable terrain are classified to consider the limitations of vehicle performance on various terrain. The non-uniform safety margin potential field (NSMPF) is proposed, based on which the non-crossable terrain source potential field (NTSPF) and the non-crossable obstacle source potential field (NOSPF) are established to quantify the risk, which can help vehicle effectively avoid unnecessary detours and save energy. The crossable obstacle source potential field (COSPF) and terrain source potential field (TSPF) are established to represent the impedimental effect of off-road environment on vehicle traveling. Finally, an application example of the MOPF in path planning is given. The MOPF has been proved by simulation to generate paths with short lengths and match the vehicle performance, while ensuring collision avoidance. In addition, the MOPF can also include different human needs and driving styles.
KW - 3D terrains
KW - artificial potential field
KW - autonomous vehicles
KW - collision avoidance
KW - path planning
UR - http://www.scopus.com/inward/record.url?scp=85190955683&partnerID=8YFLogxK
U2 - 10.1109/RICAI60863.2023.10489546
DO - 10.1109/RICAI60863.2023.10489546
M3 - Conference contribution
AN - SCOPUS:85190955683
T3 - 2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023
SP - 416
EP - 422
BT - 2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023
Y2 - 1 December 2023 through 3 December 2023
ER -