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Occupancy grid mapping basic code4/1/2024 ![]() ![]() The following code fragment is taken from the example MRPT/samples/pathPlanning. The basic usage requires declaring the gridmap, the mrpt::nav::PlannerSimple2D object, setting the robot radius, and invoking mrpt::nav::PlannerSimple2D::computePath(). For those cases, see the obstacle avoidance methods. Note that this is a very simple method, not suitable for robots with shapes very different from circular and/or moving in cluttered environmnets. The value iteration algorithm, starting at the source position, increase iteratively the area covered by shortest paths until the target cell is reached.This assure that just one single free cell is enough for the robot to move without collision. Here is a simple tutorial that shows you how to use gmapping for this use case. If you are planning to perform 2D SLAM then you could start playing around with the ROS package gmapping which will help you construct a 2D occupancy grid using LIDAR data. Growth of the obstacles by the robot radius. Yes you do need some sort of sensor data such as LIDAR data.The basic value iteration algorithm for searching shortest paths is implemented in the MRPT for occupancy grids, and circular robots, in the class mrpt::nav::PlannerSimple2D.
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