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Traditional path-planning involves (1) choosing start and goal points, (2) calculating a path, and (3) following that path. There are, however, many real world scenarios where an agent might need to change its goal and replan, which frequently includes expensively calculating a new path from scratch. We propose an adaptation to RRT∗ that locally rewires the RRT∗ tree as the robot moves and path costs...