Motion Planning in Obstacle Rich Environments

In this paper we present a multi-layer approach for motion planning in obstacle rich environments.The approach is built on the principle of separation of concern which partitions the motion planning problem into multiple independent layers. This enables design space exploration at each layer. We partition the motion planning algorithm into a roadmap layer and an optimal control layer. Elements of computational geometry are used to process the obstacle rich environment and generate a set of convex feasible regions, which is then used by the optimal control layer to generate trajectories while satisfying dynamics of the vehicle. The roadmap layer ignores the dynamics of the system, and plans paths at a global level using coarse representation of the environment. The optimal control layer ignores the complexity of the environment and plans paths at a mid-level using fine representation of the dynamics and the environment. In this manner a separation of concern is achieved. This decomposition enables computationally tractable methods to be developed for addressing motion planning in complex environments.

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