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.
2025 Energy Drone & Robotics Summit: 16–18 June 2025, HOUSTON
RSS 2025: 21–25 June 2025, LOS ANGELES
ETH Robotics Summer School: 21–27 June 2025, GENEVA
IAS 2025: 30 June–4 July 2025, GENOA, ITALY
ICRES 2025: 3–4 July 2025, PORTO, PORTUGAL
IEEE World Haptics: 8–11 July 2025, SUWON, SOUTH KOREA
IFAC Symposium on Robotics: 15–18 July 2025, PARIS
RoboCup 2025: 15–21 July 2025, BAHIA, BRAZIL
RO-MAN 2025: 25–29 August 2025, EINDHOVEN, NETHERLANDS
CLAWAR 2025: 5–7 September 2025, SHENZHEN
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!
This single-leg robot is designed to “form a foundation for future bipedal robot development,” but personally, I think it’s perfect as is.
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KAIST Dynamic Robot Control and Design Lab ]
Selling 17,000
social robots still amazes me. Aldebaran will be missed.
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Aldebaran ]
Nice to see some actual challenging shoves as part of biped testing.
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Under Control Robotics ]
Ground Control made multilegged waves at IEEE’s International Conference on Robotics and Automation 2025 in Atlanta! We competed in the Startup Pitch Competition and demoed our robot at our booth, on NIST standard terrain, and around the convention. We were proud to be a finalist for Best Expo Demo and participate in the Robot Parade.
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Ground Control Robotics ]
Thanks, Dan!
Humanoid is a U.K.-based robotics innovation company dedicated to building commercially scalable, reliable and safe robotic solutions for real-world applications.
It’s a nifty bootup screen, I’ll give them that.
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Humanoid ]
Thanks, Kristina!
Quadrupedal robots have demonstrated remarkable agility and robustness in traversing complex terrains. However, they remain limited in performing object interactions that require sustained contact. In this work, we present LocoTouch, a system that equips quadrupedal robots with tactile sensing to address a challenging task in this category: long-distance transport of unsecured cylindrical objects, which typically requires custom mounting mechanisms to maintain stability.
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LocoTouch paper ]
Thanks, Changyi!
In this video, Digit is performing tasks autonomously using a whole-body controller for mobile manipulation. This new controller was trained in simulation, enabling Digit to execute tasks while navigating new environments and manipulating objects it has never encountered before.
Not bad, although it’s worth pointing out that those shelves are not representative of any market I’ve ever been to.
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Agility Robotics ]
It’s always cool to see robots presented as an incidental solution to a problem as opposed to, you know, robots.
The question that you really want answered, though, is “Why is there water on the floor?”
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Boston Dynamics ]
Reinforcement learning (RL) has significantly advanced the control of physics-based and robotic characters that track kinematic reference motion. We propose a multi-objective reinforcement learning framework that trains a single policy conditioned on a set of weights, spanning the Pareto front of reward trade-offs. Within this framework, weights can be selected and tuned after training, significantly speeding up iteration time. We demonstrate how this improved workflow can be used to perform highly dynamic motions with a robot character.
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Disney Research ]
It’s been a week since ICRA 2025, and TRON 1 already misses all the new friends it made!
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LimX Dynamics ]
ROB 450 in Winter 2025 challenged students to synthesize the knowledge acquired through their Robotics undergraduate courses at the University of Michigan to use a systematic and iterative design and analysis process and apply it to solving a real open-ended Robotics problem.
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University of Michigan Robotics ]
What’s the Trick? A talk on human vs. current robot learning, given by Chris Atkeson at the Robotics and AI Institute.
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Robotics and AI Institute (RAI) ]
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