TY - JOUR
T1 - A Unified Framework Integrating Trajectory Planning and Motion Optimization Based on Spatio-Temporal Safety Corridor for Multiple AGVs
AU - Zang, Zheng
AU - Song, Jiarui
AU - Lu, Yaomin
AU - Zhang, Xi
AU - Tan, Yingqi
AU - Ju, Zhiyang
AU - Dong, Haotian
AU - Li, Yuanyuan
AU - Gong, Jianwei
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Planning safe and smooth trajectories for multiple autonomous ground vehicles (MAGVs) in a complex dynamic unstructured environment is a fundamental and challenging task. In this article, a novel unified framework integrating trajectory planning and motion optimization (TPMO) is proposed based on spatio-temporal safety corridor (STSC), which guarantees collision avoidance and trajectory smoothness. The proposed TPMO framework consists of two parts. The first part is to establish the STSC for each AGV based on the mixed integer quadratic programming (MIQP) algorithm. The proposed STSC method ensures collision avoidance in the environment of static and dynamic obstacles, and provides a longitudinal and lateral coupled trajectory (LLCT) for trajectory planning. The second part is to design a motion optimization methodology, which considers the constraints of AGV geometry as well as longitudinal and lateral coupled motion characteristics. Moreover, our formulation provides a theoretical guarantee that the entire trajectory is optimal under collision avoidance. Finally, the proposed TPMO framework is applied to solve the optimal cooperative trajectory and motion planning problem of MAGVs in a near-natural simulation and real vehicle environments, validating the proposed framework's effectiveness and practicality.
AB - Planning safe and smooth trajectories for multiple autonomous ground vehicles (MAGVs) in a complex dynamic unstructured environment is a fundamental and challenging task. In this article, a novel unified framework integrating trajectory planning and motion optimization (TPMO) is proposed based on spatio-temporal safety corridor (STSC), which guarantees collision avoidance and trajectory smoothness. The proposed TPMO framework consists of two parts. The first part is to establish the STSC for each AGV based on the mixed integer quadratic programming (MIQP) algorithm. The proposed STSC method ensures collision avoidance in the environment of static and dynamic obstacles, and provides a longitudinal and lateral coupled trajectory (LLCT) for trajectory planning. The second part is to design a motion optimization methodology, which considers the constraints of AGV geometry as well as longitudinal and lateral coupled motion characteristics. Moreover, our formulation provides a theoretical guarantee that the entire trajectory is optimal under collision avoidance. Finally, the proposed TPMO framework is applied to solve the optimal cooperative trajectory and motion planning problem of MAGVs in a near-natural simulation and real vehicle environments, validating the proposed framework's effectiveness and practicality.
KW - Spatio-temporal safety corridor
KW - longitudinal and lateral coupling trajectory
KW - trajectory planning and motion optimization
UR - http://www.scopus.com/inward/record.url?scp=85162722375&partnerID=8YFLogxK
U2 - 10.1109/TIV.2023.3285911
DO - 10.1109/TIV.2023.3285911
M3 - Article
AN - SCOPUS:85162722375
SN - 2379-8858
VL - 9
SP - 1217
EP - 1228
JO - IEEE Transactions on Intelligent Vehicles
JF - IEEE Transactions on Intelligent Vehicles
IS - 1
ER -