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CostTrust: A Fast-Exploring, Iteratively Expanding Frontier-Based Kinodynamic Motion Planner
Ist Teil von
Modeling, identification and control, 2024, Vol.45 (1), p.15-28
Ort / Verlag
Norwegian Society of Automatic Control
Erscheinungsjahr
2024
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
Sampling-based motion planning has recently experienced considerable advancements, particularly in the domain of geometric motion planning for diverse robotic systems. Nonetheless, kinodynamic motion planning, which additionally considers a robot's kinematics and dynamics to generate a motion plan, remains an open challenge, necessitating further research. Kinodynamic planning, inherently more complex than geometric planning, mandates that the planner not only adheres to motion constraints but also account for system dynamics, including limitations in velocity and acceleration. Furthermore, kinodynamic planning often requires the navigation of extensive state and control spaces, rendering the process both computationally demanding and time-consuming. To effectively tackle kinodynamic motion planning, our proposed approach introduces a dynamic balance between exploration and exploitation, continuously adjusted throughout the execution. Our bi-directional and multi-threaded algorithm is specifically tailored to fulfill the efficiency requisites of kinodynamic motion planning. Our comprehensive benchmarks, conducted on an Ackermann-steered robot and a dynamic quadrotor, demonstrate that our method notably outperforms state-of-the-art baselines in terms of solution rate percentage and path cost. To facilitate accessibility and further research within the community, we have made the implementation of our method available. It is integrated with the Open Motion Planning Library (OMPL), a widely utilized resource in the field, enhancing our approach's practical applicability.