TY - JOUR
T1 - A Reachability-Based Spatio-Temporal Sampling Strategy for Kinodynamic Motion Planning
AU - Tang, Yongxing
AU - Zhu, Zhanxia
AU - Zhang, Hongwen
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - By limiting the planning domain to 'L2 Informed Set', some sampling-based motion planners (SBMP) (e.g., Informed RRT∗, BIT∗) can solve the geometric motion planning problems efficiently. However, the construction of informed set (IS) will be very challenging, when further differential constraints are considered. For the time-optimal kinodynamic motion planning problem, this paper defines a modified time informed set (MTIS) to limit the planning domain. Due to drawing inspiration from Hamilton-Jacobi-Bellman (HJB) reachability analysis, MTIS, compared with the original TIS, can not only help save the running time of SBMP, but also extend the applicable scope from linear systems to polynomial nonlinear systems with control constrains. On this basis, a spatio-temporal sampling strategy adapted to MTIS is proposed. Firstly, MTIS is used to estimate the optimal cost and the valid tree structure is reused, so that we do not need to provide a solution trajectory in advance. Secondly, this strategy is generic, allowing it to be combined with common SBMP (such as SST, etc.) to accelerate convergence and reduce the memory requirement. Several simulation experiments also demonstrate the effectiveness of proposed method.
AB - By limiting the planning domain to 'L2 Informed Set', some sampling-based motion planners (SBMP) (e.g., Informed RRT∗, BIT∗) can solve the geometric motion planning problems efficiently. However, the construction of informed set (IS) will be very challenging, when further differential constraints are considered. For the time-optimal kinodynamic motion planning problem, this paper defines a modified time informed set (MTIS) to limit the planning domain. Due to drawing inspiration from Hamilton-Jacobi-Bellman (HJB) reachability analysis, MTIS, compared with the original TIS, can not only help save the running time of SBMP, but also extend the applicable scope from linear systems to polynomial nonlinear systems with control constrains. On this basis, a spatio-temporal sampling strategy adapted to MTIS is proposed. Firstly, MTIS is used to estimate the optimal cost and the valid tree structure is reused, so that we do not need to provide a solution trajectory in advance. Secondly, this strategy is generic, allowing it to be combined with common SBMP (such as SST, etc.) to accelerate convergence and reduce the memory requirement. Several simulation experiments also demonstrate the effectiveness of proposed method.
KW - constrained motion planning
KW - Motion and path planning
KW - optimization and optimal control
UR - https://www.scopus.com/pages/publications/85144017268
U2 - 10.1109/LRA.2022.3226032
DO - 10.1109/LRA.2022.3226032
M3 - 文章
AN - SCOPUS:85144017268
SN - 2377-3766
VL - 8
SP - 448
EP - 455
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 1
ER -