Abstract
The development of service robots has recently received considerable attention. Their deployment, however, normally involves a substantial programming effort to develop a particular application. With the incorporation of service robots to daily activities, it is expected that they will require to perform different tasks. Fortunately, many of such applications share common modules such as navigation, localization and human interaction, among others. In this chapter, a general framework to easily develop different applications for service robots is presented. In particular, we have developed a set of general purpose modules for common tasks that can be easily integrated into a distributed, layered architecture, and coordinated by a decision–theoretic planner to perform different tasks. The coordinator is based on a Markov decision process (MDP) whose reward is set according to the task’s goal, the states are represented by a set of variables affected by the general modules, and the actions correspond to the execution of the different modules. In order to create a new application the user only needs to define a new MDP whose solution provides an optimal policy that coordinates the different behaviors for performing the task. The effectiveness of our approach is experimentally demonstrated in four different service robot tasks with very promising results. Additionally, several aspects include some novel ideas; in particular in navigation, localization and gesture recognition.
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Avilés-Arriaga, H.H., Sucar, L.E., Morales, E.F., Vargas, B.A., Sánchez, J., Corona, E. (2009). Markovito: A Flexible and General Service Robot. In: Liu, D., Wang, L., Tan, K.C. (eds) Design and Control of Intelligent Robotic Systems. Studies in Computational Intelligence, vol 177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89933-4_19
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DOI: https://doi.org/10.1007/978-3-540-89933-4_19
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