Boston Dynamic’s robot Spot the dog learns to dance
Teaching robots to dance helps researchers fine tune robots motor skills so they can be more agile and dextrous.
Key takeaways
- The overall idea is to emulate improvisation, in the same way that human dancers adaptively string together a series of different moves with transitions in between.
- Once the robot has an idea for the dance moves that it wants to perform, the really tricky bit is performing those moves such that they properly land on the beat.
- Spot, for one, seems talented enough that it’s able to keep the beat even when it’s being shoved around, or when the surface that it’s standing on changes abruptly.
Cite or link to this article
Griffin, M. (2019) 'Boston Dynamic’s robot Spot the dog learns to dance', 311 Institute, 6 February. Available at: https://www.311institute.com/boston-dynamics-robot-spot-the-dog-learns-to-dance/ (Accessed: 1 October 2026).
At IROS in Madrid, Marc Raibert from Boston Dynamics, one of the world’s most advanced robotics companies, showed a few videos during his keynote presentation. One was of Atlas, the world’s most advanced humanoid robot, running through parks and doing parkour, which I wrote about a while ago, and the other was just a brief clip of SpotMini, Boston Dynamic’s robot dog sensation, dancing.
Now though the company has posted a new video of SpotMini, which they’re increasingly referring to as simply “Spot,” dancing to Uptown Funk, and frankly displaying more talent than the original human performance. The twerking is cute, but gets a little weird when you realize that SpotMini’s got some eyeballs back there as well.
Dog's got moves
While we don’t know exactly what’s going on in this video, as with many of Boston Dynamics’ video, my guess would be that these are a series of discrete, scripted behaviours that are played in sequence. They’re likely interchangeable and adaptable to different beats, but, again, as with many of their videos, it’s not clear to what extent these dancing behaviours are autonomous and off the cuff, and how Spot would react to a different song.
Oddly though the guys and gals at ETH Zurich thought this would be an ideal time to write a paper on “Real-Time Dance Generation to Music for a Legged Robot.” Why write a paper on this you ask… well, apparently it’s because people like dancing and researchers think that that should then automatically mean people like dancing robots. We’ll see.
“Dance, as a performance art form, has been part of human social interaction for multiple millennia. It helps us express emotion, communicate feelings and is often used as a form of entertainment. Consequently, this form of interaction has often been attempted to be imitated by robots,” says the paper, before adding, “The researchers goal with [this work] is to bridge the gap between the ability to react to external stimuli, in this case music, and the execution of dance motions that are both synchronized to the beat, and visually pleasing and varied.”
The first step to creating a dancing robot is a beat tracker, which requires the robot to listen to music for between 1 second and 8 seconds, depending on how dominant the beat is. Once the beat is detected, a dance choreographer program builds dance moves by choosing dance motion “primitives” from a library. These primitives include parameters like repeatability, duration, trajectory amplitude, and tempo range, to help the program keep the overall choreography interesting. The overall idea is to emulate improvisation, in the same way that human dancers adaptively string together a series of different moves with transitions in between.
Once the robot has an idea for the dance moves that it wants to perform, the really tricky bit is performing those moves such that they properly land on the beat. For example, depending on how the robot’s limbs are positioned, the time that it takes for it to take a step in a particular direction can change, meaning that the robot has to predict how long each dance move will take to execute and plan its timing accordingly to compensate for the delay caused by actuators and motion and physics and all that stuff. Spot, for one, seems talented enough that it’s able to keep the beat even when it’s being shoved around, or when the surface that it’s standing on changes abruptly.
“We have successfully built the foundation for a fully autonomous, improvising and synchronized dancing robot. Nevertheless, the robot is still limited in its ability to entertain for a long duration and appears robot-like, due to its still limited variation in dance choreography. Future work can be done to achieve our ultimate goal of building a system, which outputs natural human-like dance, with great variations in movement and seamless transitions from one song to another,” said Raibert.
So, as the competition to create realistic dancing robots that jig to the beat all by themselves heats up I’m sure that this won’t be the last video we see of a robot dancing to some odd tune, so stay tuned. If you dare.
What this means for your organisation
Dance shows fine control.
Moving in time with music demands balance and precise timing. Those same skills help robots work on uneven ground and around people. Entertainment demos reveal real capability.
Reacting to the world is the goal.
Researchers want robots to respond to outside signals, not just play scripts. That is what useful work requires. Watch for robots that adapt on the fly.
Public appeal matters.
Likeable robots are easier to bring into homes, shops and events. Fun demos build acceptance. Firms planning service robots should consider how they will be received.
Three questions for your next leadership meeting
- Where could agile legged robots work on our sites?
- Do our robots need to react to changing conditions?
- How would customers respond to robots in our spaces?
The trends and technologies behind this story
From the 311 Starburst, the 311 Strategic Intelligence Unit’s map of the technologies and trends shaping the next 50 years.
Analysis by the 311 Strategic Intelligence Unit, from Matthew Griffin’s article and 311 data. First published on Fanatical Futurist.
FAQ
Why does this matter?
Teaching robots to dance helps researchers fine tune robots motor skills so they can be more agile and dextrous.

About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 17-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- Spotmini robots.ieee.org
Source: first published by the 311 Institute on 6 February 2019. Cite as: Griffin, M. (2019). Boston Dynamic’s robot Spot the dog learns to dance. 311 Institute. https://www.311institute.com/boston-dynamics-robot-spot-the-dog-learns-to-dance/
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