Teknik Pengenalan Suara Musik pada Robot Seni Tari

The dancing robot has become an annual competition in Indonesia that needs to be developed to improve robot performance. The dancing robot is a humanoid robot that has 24 degrees of freedom. For 2018 the theme raised was "Remo Dancer Robot". Sound processing provides a very important role in dance robots. This robot moves dancing to adjust to the rhythm of the music. The robot will stop dancing when the music is mute. The resulting sound signal is still analogous. Voice signals must be changed to digital data to access the signal. Convert analog to digital signals using Analog Digital Converter (ADC). ADC data is taken by sampling time 254 data per second. The sampling data is stored and grouped per 1 second to classify the parts of Remo Dance music. The results of data classification are in the form of digital numbers which then become a reference to determine the movement of the robot. Robots can recognize conditions when music is in a mute or a play condition

How does peoples’ perception of control depend on the criticality of a task performed by a robot Paladyn

© 2019 Adeline Chanseau et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 Public License.Robot companions are starting to become more common and people are becoming more familiar with devices such as Google Home, Alexa or Pepper,one must wonder what is the optimum way for people to control their devices? This paper provides presents an investigation into how much direct control people want to have of their robot companion and how dependent this is on the criticality of the tasks the robot performs. A live experiment was conducted in the University of Hertfordshire Robot House, with a robot companion performing four different type of tasks. The four tasks were: booking a doctor’s appointment, helping the user to build a Lego character, doing a dance with the user, and carrying biscuits for the user. The selection of these tasks was based on our previous research to define tasks which were relatively high and low in criticality. The main goal of the study was to find what level of direct control over their robot participants and if this was dependent on the criticality of the task performed by the robot. Fifty people took part in the study, and each experienced every task in a random order. Overall,it was found that participants’ perception of control was higher when the robot was performing a task in a semi-autonomous mode. However, for the task "carrying biscuits", although participants perceived to be more in control with the robot performing the task in a semi autonomous mode, they actually preferred to have the robot performing the task automatically (where they felt less in control). The results also show that, for the task "booking a doctor’s appointment", considered to be the most critical of all four tasks, participants did not prefer that the robot chose the date of the appointment as they felt infantilised.Peer reviewe

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

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