Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
CLAWAR 2025: 5–7 September 2025, SHENZHEN, CHINA
ACTUATE 2025: 23–24 September 2025, SAN FRANCISCO
CoRL 2025: 27–30 September 2025, SEOUL
IEEE Humanoids: 30 September–2 October 2025, SEOUL
World Robot Summit: 10–12 October 2025, OSAKA, JAPAN
IROS 2025: 19–25 October 2025, HANGZHOU, CHINA
Enjoy today’s videos!
Boston Dynamics is back and their dancing robot dogs are bigger, better, and bolder than ever! Watch as they bring a “dead” robot to life and unleash a never before seen synchronized dance routine to “Good Vibrations.”
And much more interestingly, here’s a discussion of how they made it work:
[ Boston Dynamics ]
I don’t especially care whether a robot falls over. I care whether it gets itself back up again.
[ LimX Dynamics ]
The robot autonomously connects multiple wires to the environment using small flying anchors—drones equipped with anchoring mechanisms at the wire tips. Guided by an onboard RGB-D camera for control and environmental recognition, the system enables wire attachment in unprepared environments and supports simultaneous multi-wire connections, expanding the operational range of wire-driven robots.
[ JSK Robotics Laboratory ] at [ University of Tokyo ]
Thanks, Shintaro!
For a robot that barely has a face, this is some pretty good emoting.
[ Pollen ]
Learning skills from human motions offers a promising path toward generalizable policies for whole-body humanoid control, yet two key cornerstones are missing: (1) a scalable, high-quality motion tracking framework that faithfully transforms kinematic references into robust, extremely dynamic motions on real hardware, and (2) a distillation approach that can effectively learn these motion primitives and compose them to solve downstream tasks. We address these gaps with BeyondMimic, a real-world framework to learn from human motions for versatile and naturalistic humanoid control via guided diffusion.
[ Hybrid Robotics ]
Introducing our open-source metal-made bipedal robot MEVITA. All components can be procured through e-commerce, and the robot is built with a minimal number of parts. All hardware, software, and learning environments are released as open source.
[ MEVITA ]
Thanks, Kento!
I’ve always thought that being able to rent robots (or exoskeletons) to help you move furniture or otherwise carry stuff would be very useful.
[ DEEP Robotics ]
A new study explains how tiny water bugs use fan-like propellers to zip across streams at speeds up to 120 body lengths per second. The researchers then created a similar fan structure and used it to propel and maneuver an insect-sized robot. The discovery offers new possibilities for designing small machines that could operate during floods or other challenging situations.
[ Georgia Tech ]
Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. To achieve generalized legged locomotion on diverse terrains while preserving the robustness of learning-based controllers, this paper proposes to learn an attention-based map encoding conditioned on robot proprioception, which is trained as part of the end-to-end controller using reinforcement learning. We show that the network learns to focus on steppable areas for future footholds when the robot dynamically navigates diverse and challenging terrains.
[ Paper ] from [ ETH Zurich ]
In the fifth installment of our Moonshot Podcast Deep Dive video interview series, X’s Captain of Moonshots Astro Teller sits down with Google DeepMind’s Chief Scientist Jeff Dean for a conversation about the origin of Jeff’s pioneering work scaling neural networks. They discuss the first time AI captured Jeff’s imagination, the earliest Google Brain framework, the team’s stratospheric advancements in image recognition and speech-to-text, how AI is evolving, and more.
[ Moonshot Podcast ]
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