This paper presents a scalable method for friction identification in robots equipped with electric motors and high-ratio harmonic drives, utilizing Physics-Informed Neural Networks (PINN). This approach eliminates the need for dedicated setups and joint torque sensors by leveraging the robo\v{t}s intrinsic model and state data. We present a comprehensive pipeline that includes data acquisition, preprocessing, ground truth generation, and model identification. The effectiveness of the PINN-based friction identification is validated through extensive testing on two different joints of the humanoid robot ergoCub, comparing its performance against traditional static friction models like the Coulomb-viscous and Stribeck-Coulomb-viscous models. Integrating the identified PINN-based friction models into a two-layer torque control architecture enhances real-time friction compensation. The results demonstrate significant improvements in control performance and reductions in energy losses, highlighting the scalability and robustness of the proposed method, also for application across a large number of joints as in the case of humanoid robots.

It's been two years since the last time I judged the Automate Startup Competition. More than any other trade show contest, this event has been an oracle of future success. In following up with the last vintage of participants, all of the previous entrees are still operating and many are completing multi-million dollar financing rounds. As an indication of the importance of the venue, and quite possibly the growth of the industry, The Robot Report announced last week that 2017 finalist, Kinema Systems was acquired by SoftBank's Boston Dynamics. Traditionally, autonomous machines at the ProMat Show have been relegated to a subsection of the exhibit floor under the Automate brand.

In the wake of the closure of Apple's autonomous car division (Project Titan) this week, one questions if Steve Jobs' axiom still holds true. "Some people say, 'Give the customers what they want.' Our job is to figure out what they're going to want before they do," declared Jobs and continued with an analogy, "I think Henry Ford once said, 'If I'd asked customers what they wanted, they would have told me, 'a faster horse!'" Titan joins a growing graveyard of autonomous innovations, which is filled with the tombstones of Baxter, Jibo, Kuri and many broken quadcopters. If anything holds true, not every founder is Steve Jobs or Henry Ford and listening to public sentiment could be a bellwether for success. Adam Jonas of Morgan Stanley announced on January 9, 2019 from the Consumer Electronic Show (CES) floor, "It's official. It's the timing… the telemetry of adoption for L5 cars without safety drivers expected by many investors may be too aggressive by a decade… possibly decades."

I know, it doesn't seem like there's any possible way that a transmission system could be interesting enough that we'd dedicate an entire article (and video!) to it. But here we are: As soon as SRI explained how their new Abacus transmission worked, we were absolutely sure that it was cool enough to share. In a nutshell, here's why: It's the first new rotary transmission design since Harmonic Drive introduced its revolutionary gear system in the 1960s*, and it might give harmonic gears a literal run for their money. The physics of most electric motors generally dictates that the motors are happiest when they're spinning very fast. Unless you want to use them to simply spin a thing very fast, you'll need to add a rotary transmission that can convert low torque, high speed rotation into higher torque, lower speed rotation. If you've got the budget, the way to do this is with a high-performance harmonic gear like the ones offered by Harmonic Drive.