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how to do path planning in 3d numpy array? #36


I have a 3d segmentation map(3d numpy array) which has obstacles and target ,how can i do planning with rrt in this image ,can you please give a refrence example for this?also how to convert this numpy array to a state space containing obstacles ?

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You would need to subclass the CSpace class and implement the feasible(q), bound, and eps members. See the docs here for more information.

The feasible(q) callback is the essential function to determine whether a point q=[x,y,z] is in collision or not. In other words, it implicitly represents obstacles by returning False when the point is in collision.