Cheek to Chip: Dancing Robots and Al’s Future

Cheek to Chip: Dancing Robots and Al’s Future

1. INTRODUCTION

   • Music and dancing are activities best known human entertainment, and are linked to the ability to socialize. The sound and movement patterns characterize the dance.
     • Robots That Learn to Dance from Observation
       • This
         • Recent generations of humanoid robots increasingly resemble humans
           • This progress
             • Has led researchers to design robots that can mimic dancers complexity and style of dance choreography human.
     • It allows
       • the robot what to do and how to do it from observation. The model is divided into two legs.
       • At the end they concatenate the two and dynamic filters are applied to prevent the robot hit with it.

2. for this

   • Researchers at the University of Tokyo have developed the learning-from-observation (LFO) training method
     • Generating upper-body motion
       • use the same task-model strategy as for leg motions. In this case, each model represents a key pose of the imitated dance.
     • Generating whole-body motion
       • To generate executable motion, we use a dynamic filter and conduct skill refinement. The dynamic filter compensates the zero-moment point and the yaw-axis moment
     • Motion from Sound: Intermodal Neural Network Mapping
       • Robots that interact with humans must be able to react to multimodal sensory input.
       • Intermodality mapping
         • consists of
           • two phases. First, in the learning phase, the robot observes some events together with associated sounds. The robot memorizes these sounds along with the motions of the sound source
             • Keepon
               • uses signal processing techniques and accelerometers to detect movements of the person
             • Dance Partner
               • It uses a database of knowledge and estimates to predict the movement
         • Control system architecture
           • uses
             • Step transitions that is, when and how the human partner changes steps in a dance sequence are important for the robot to generate its own dancing motion