Juan M. Calderón

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In this paper, we perform a comparison between classical PI+D control strategies with a fuzzy modified PI+D control. The fuzzy PI+D controller is a discrete-time version of the conventional PI+D controller, which has constant coefficients of self-tuned control gains. The proposed control strategies were tested using a mathematical model based on a bipedal(More)
This paper shows the results of applying machine learning techniques to the problem of predicting soccer plays in the Small Size League of RoboCup. We have modeled the task as a multi-class classification problem by learning the plays of the STOx's team. For this, we have created a database of observations for this team's plays and obtained key features(More)
In this paper we describe the design and implementation of an educational methodology based on a robotic platform used for the small size league (SSL) challenge of the RoboCup initiative. The methodology is based on three main aspects of the learning process, namely classical conditioning, reinforcement learning and cognitive learning. This is achieved(More)
— In this study the current usage of each associated joint of a humanoid robot (NAO) during stand up process is analyzed. This study is the extension of our previous study [1] where the energy consumption of single and overall joints of a NAO robot during the walking process was researched while keeping the same stiffness values for all joints. This paper(More)