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Authors propose trajectory bundle graph nonlinear motion planning method
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Joris Verhagen and other authors propose the trajectory bundle graph (GTB) method, which combines sampling-based motion planning, trajectory optimization, and graph search for motion planning of nonlinear and even black-box dynamical systems. The method first decomposes the workspace into a convex set graph, then iteratively constructs a trajectory bundle graph to characterize the local dynamics at each vertex; subsequently, it solves a shortest-path problem on the graph to obtain trajectories that, in the limit, satisfy the system dynamics as well as collision, safety, and other constraints. The authors state that the method can handle highly nonlinear, unstable, or even black-box dynamics and complex constraints.
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- GTB: A Trajectory Bundle Graph Motion Planning Method for Nonlinear Dynamics
The authors propose the Graphs of Trajectory Bundles (GTB) method, which combines sampling-based motion planning, trajectory optimization, and graph search for motion planning of systems with nonlinear and even black-box dynamics. Based on a graph-of-convex-sets decomposition of the workspace, the method iteratively constructs a graph of trajectory bundles that captures the local dynamics at each vertex, then solves a shortest-path problem on the graph to obtain trajectories that satisfy the system dynamics and constraints such as collision avoidance and safety in the limit. The authors claim it can handle highly nonlinear, unstable, and even black-box dynamics with complex constraints.
arXiv cs.RO ·