Motion planning


For more advanced motion planning algorithms, refer to the selfdriving library.

1. Path planning for circular robots and 2D grid maps

The basic value iteration algorithm for searching shortest paths is implemented in MRPT for circular robots and obstacles described by means of occupancy grids in the class mrpt::nav::PlannerSimple2D.

The method comprises two steps:

  • Growth of the obstacles by the robot radius. This assure that just one single free cell is enough for the robot to move without collision.

  • The value iteration algorithm, starting at the source position, increase iteratively the area covered by shortest paths until the target cell is reached.

Note that this is a very simple method, not suitable for robots with shapes very different from circular and/or moving in cluttered environments. For those cases, see the obstacle avoidance methods above.

Using this planner requires declaring the gridmap, the mrpt::nav::PlannerSimple2D object, setting the robot radius, and invoking mrpt::nav::PlannerSimple2D::computePath(). See the complete example source code here.


2. RRT path planning

3. Obstacle avoidance (reactive navigation)