**5. Conclusions and perspectives**

**Figure 17.** Real robot performance. (a) Robot path to the box location and (b) robot takes the box.

184 Advanced Path Planning for Mobile Entities

**Figure 18.** Path to move the robot from (2,2) to (8,3) cells, without obstacles in the environment.

The task of moving an object from one place to another in an autonomous way requires many considerations: the mobile robot, the mechanism used to carry the object, the path planning strategy, and synchronization of all the systems involved in the task. In this chapter, the robotic NXT arm can be programmed at a maximal distance of 10 m. and some of the considerations to implement this kind of project are:


An appropriate space must be found for robot navigation purposes to avoid excessive or deficient friction of the wheels against the floor, to establish speeds and distances.

The overall strategy programmed on the mobile robot should encourage beginners or young people interested in robotic developments. We are currently working on the integration of a method to verify if the second phase of the trajectory can be performed as initially established. In addition, we are also correcting odometric mistakes at a mechanical level. On both platforms, DaNI robot and NXT, LabView and LabView robotic modules are used respectively to program communication between the robotic arm and the mobile robot using the same rules of code. Finally, a perspective to increase the accuracy of the navigation consists in adding a video camera to monitor the palletizing process.

[11] Rico JM. Analisis dinamico de un mecanismo plano de cuatro barras. Analisys of Mechanisms, undergraduate course. Division de Ingenierias Campus Irapuato-Salamanca,

Design and Implementation of a Demonstrative Palletizer Robot with Navigation…

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[15] Trimble: How to use Google-sketchup, Trimble Corporate and SketchUp developers. Available from: https://www.sketchup.com/learn/videos/826 [Accessed: 14-08-2017] [16] Dechter R, Judea P. Generalized best-first search strategies and the optimality of A\*.

[17] Ferguson D, Likhachev M, Stentz A.A guide to heuristic-based path planning. Proceedings of ICAPS Workshop on Planning under Uncertainty for Autonomous Systems; 2005. www.cs.cmu.edu/afs/cs.cmu.edu/Web/People/maxim/files/hsplanguide\_icaps05ws.pdf

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