Similar to humans, this robot can listen to music and is able to perform it after only two minutes of self-training.
The successful experiments indicate a new paradigm for rehabilitation robotics, rooted in experiential learning.
In a neuro-robotics laboratory at the University of Southern California, a small mechanical hand heard a melody for the first time and successfully played it back on the first attempt, without any sheet music, pre-loaded scores, or extended supervised training (via USC Viterbi).
This system is referred to as the Musician Hand. It features four fingers, each operated by a tendon linked to a small electric motor, resembling the way muscles pull tendons in a human hand. It was developed by doctoral candidate Hesam Azadjou under the guidance of Professor Francisco Valero-Cuevas.
How did the robot learn this skill?
The learning process involved a method known as "motor babbling," which mimics the exploratory trial-and-error techniques that humans employ to master control over their limbs. Without any understanding of hands, keyboards, or music, the robot discovered that it could create sounds by pressing piano keys.
Initially, the robotic hand randomly pressed keys for two minutes, studying the association between finger movements and the sounds produced by the piano. From this short experience, it established the connection between motor commands (the finger movements) and outcomes (the sounds).
Upon hearing a melody of about 30 notes for the first time, created by Los Angeles-based composer Richard Tuttobene and titled “Robo Algo,” the Musician Hand converted the audio into a spectrogram, utilized neural networks to recognize the notes, and then generated the necessary commands to recreate the sequence successfully on the initial try.
What makes this more than just a musical novelty?
The researchers also held a blind audition where two judges evaluated the Musician Hand alongside four trained pianists without knowing which was the robot. At times, they could not differentiate between the human musicians and the robot.
In contrast, untrained individuals were unable to replay even the first few notes. Azadjou highlights that the human brain can solve complex motor challenges using less than 100 watts of power, comparable to a laptop charger, while conventional AI may require megawatt levels of power for similar tasks.
This type of streamlined, efficient, and experiential based learning could be utilized in wearable robotic devices for everyday use, such as exoskeletons for individuals with Parkinson's and personalized rehabilitation robots. This research received backing from the NSF and DARPA.
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Similar to humans, this robot can listen to music and is able to perform it after only two minutes of self-training.
USC's Musician Hand learned to play the piano by ear in just two minutes through a process resembling infant motor babbling.