Implementation and comparison in local planners for Ackermann vehicles

Motion control plays an important role in autonomous navigation. It can be de ned as the compute of motion control inputs for a collision-free path tracking. To perform the motion control in path planning, a local planner is used. A good local planner should take into consideration the capabilities of the vehicle (kinematic and dynamic constraints), in order to compute feasible movements for the robot. This work is focused on the local planning problem for non-holonomic vehicles in an (x; y; ) space. Three local planners using di erent methods to compute the command velocities are implemented in the Robot Operating System (ROS) framework, widely used in the robotics community. To ful ll our goal, three ROS nodes are created, the rst one uses the Dynamic Windows Approach algorithm to compute the command velocities. The second uses the Timed Elastic Band algorithm. The third uses the Model Predictive Control algorithm. To deal with the non-holonomic vehicle constraints, an Ackermann kinematic model is used. IXOutgoin