Boston Dynamics loves showing off their robots with dance videos. Every time they put one out, it ignites a discussion among robot enthusiasts debating what’s real versus merely implied by the exhibition. We really want to see tooling behind the scenes and fortunately we get a peek with a Spot dance choreography session posted by [Adam Savage]’s Tested team. (YouTube video, also embedded below.)
For about a year, the Tested team has been among those exploring a Spot’s potential. Most of what we’ve seen has been controlled from a custom tablet that looked like a handheld video game console. In contrast, this video shows a computer application for sequencing Spot actions on a music-focused timeline. The timer period is specified in beats per minute, grouped up eight to a bar. The high level task is no different from choreographing human dancers: design something that can be performed to music, delights your audience, all while staying within the boundaries of what your dancers can physically do with their bodies. Then, trust your dancers to perform!
That computer application is Boston Dynamics Choreographer, part of the Spot Choreography SDK. A reference available to anyone who is willing to Read The Fine Manual even if we don’t have a Spot of our own. As of this writing, Choreography SDK covers everything we saw Spot do in an earlier UpTown Funk dance video, but looks like it has yet to receive some of the more advanced Spot dances in the recent Do You Love me? video. There is a reference chart of moves illustrated with animated GIF, documented with customizable parameters along with other important notes.
We’ve seen a lot of hackers take on the challenge of building their own quadruped robots on these pages. Each full of clever mechanical design solutions that can match Spot’s kinematics. And while not all of them can match Spot’s control systems, we’re sure it’s only a matter of time before counterparts to Choreographer application show up on GitHub. (If they already exist, please link in comments.) Will we love robots once they can all dance? The jury is still out.
Continue reading “Start Your New Career In Robot Dance Choreography”
Do you have a great application for computer vision, but couldn’t spare the cost of hardware needed to build it? Or perhaps you just need a deadline to pull you away from endless doom scrolling? Either way, the OpenCV team wants you to enter their OpenCV AI Competition 2021 and they’re willing to pitch in hardware to make it happen.
This competition is part of OpenCV’s 20th anniversary celebration, and the field of machine vision has changed a lot in those two decades. OpenCV started within Intel harnessing power of their high end CPUs, but today the excitement is around specialized acceleration hardware for vision processing. Which is why OpenCV put their support and lent their name to the OpenCV AI Kit (OAK) Kickstarter we covered a few months ago. Since then, the hardware was produced and starting to arrive in project backer’s hands. (Barring pandemic-related shipping restrictions…)
This shiny new hardware is the competition’s focus. Phase one solicits team proposals for putting an OAK-D’s power to novel use. University teams may have up to ten members, general teams are limited to four. Each team’s geographic home will put them in one of six global regions. Proposals must be submitted by January 27th, 2021. By February 11th, judges will select the best twenty-five general and ten university team proposals from each region, and every member of the team gets an OAK-D unit to turn their idea into reality by phase two deadline of June 27th. That’s up to 1,200 OAK-D modules available to anyone who can convince the judges they have a great idea and they are capable of bringing it to fruition. Is that you? Of course it is!
Teams will also receive additional resources such as an allotment of cloud compute credits to train their models, and naturally all tutorials and sample code released as part of OAK Kickstarter. No explicit resource for project team organization is mentioned, but of course our own Hackaday.io is available to support you. Best of luck to everyone who enters and we look forward to seeing all the projects this contest will bring to life.
Humanoid robots always attract attention, but anyone who tries to build one quickly learns respect for a form factor we take for granted because we were born with it. Pollen Robotics wants to help move the field forward with Reachy: a robot platform available both as a product and as a wealth of information shared online.
This French team has released open source robots before. We’ve looked at their Poppy robot and see a strong family resemblance with Reachy. Poppy was a very ambitious design with both arms and legs, but it could only ever walk with assistance. In contrast Reachy focuses on just the upper body. One of the most interesting innovations is found in Reachy’s neck, a cleverly designed 3 DOF mechanism they called Orbita. Combined with two moving antennae at the top of the head, Reachy can emote a wide range of expressions despite not having much of a face. The remainder of Reachy’s joints are articulated with Dynamixel serial bus servos though we see an optional Orbita-based hand attachment in the demo video (embedded below).
Reachy’s € 19,990 price tag may be affordable relative to industrial robots, but it’s pretty steep for the home hacker. No need to fret, those of us with smaller bank accounts can still join the fun because Pollen Robotics has open sourced a lot of Reachy details. Digging into this information, we see Reachy has a Google Coral for accelerating TensorFlow and a Raspberry Pi 4 for general computation. Mechanical designs are released via web-based Onshape CAD. Reachy’s software suite on GitHub is primarily focused on Python, which allows us to experiment within a Jupyter notebook. Simulation can be done within Unity 3D game engine, which can be optionally compiled to run in a browser like the simulation playground. But academic robotics researchers are not excluded from the fun, as ROS1 integration is also available though ROS2 support is still on the to-do list.
Reachy might not be as sophisticated as some humanoid designs we’ve seen, and without a lower body there’s no way for it to dance. But we are very appreciative of a company willing to share knowledge with the world. May it spark new ideas for the future.
Continue reading “Reachy The Open Source Robot Says Bonjour”
We don’t know how much time passed between the invention of the wheel and someone putting wheels on their feet, but we expect that was a great moment of discovery: combining the ability to roll off at speed and our leg’s ability to quickly adapt to changing terrain. Now that we have a wide assortment of recreational wheeled footwear, what’s next? How about teaching robots to skate, too? An IEEE Spectrum interview with [Marko Bjelonic] of ETH Zürich describes progress by one of many research teams working on the problem.
For many of us, the first robot we saw rolling on powered wheels at the end of actively articulated legs was when footage of the Boston Dynamics ‘Handle’ project surfaced a few years ago. Rolling up and down a wide variety of terrain and performing an occasional jump, its athleticism caused quite a stir in robotics circles. But when Handle was introduced as a commercial product, its job was… stacking boxes in a warehouse? That was disappointing. Warehouse floors are quite flat, leaving Handle’s agility under-utilized.
Boston Dynamic has typically been pretty tight-lipped on details of their robotics development, so we may never know the full story behind Handle. But what they have definitely accomplished is getting a lot more people thinking about the control problems involved. Even for humans, we face a nontrivial learning curve paved with bruised and occasionally broken body parts, and that’s even before we start applying power to the wheels. So there are plenty of problems to solve, generating a steady stream of research papers describing how robots might master this mode of locomotion.
Adding to the excitement is the fact this is becoming an area where reality is catching up to fiction, as wheeled-legged robots have been imagined in forms like Tachikoma of Ghost in the Shell. While those fictional robots have inspired projects ranging from LEGO creations to 28-servo beasts, their wheel and leg motions have not been autonomously coordinated as they are in this generation of research robots.
As control algorithms mature in robot research labs around the world, we’re confident we’ll see wheeled-legged robots finding applications in other fields. This concept is far too cool to be left stacking boxes in a warehouse.
Continue reading “Legged Robots Put On Wheels And Skate Away”
One of Hyundai’s recent concept cars was an electric vehicle named “45” in honor of its inspiration, another concept car from 45 years ago. When footage of a child-sized “Mini 45” surfaced, it was easy to conclude the car was a motorized toy for children. But Jalopnik got more information from Hyundai about this project, where we learned that was not nearly the whole picture.
The video (embedded below) explained this little vehicle is a concept car in its own right, and most of the video is a scripted performance illustrating their concept: using technology to help calm young patients in a hospital, reducing their anxiety as they faced treatment procedures. Mini 45 packs a lot more equipment than the toy cars available at our local store. The little driver’s heartbeat and breathing rate are monitored, and a camera analyzes facial expressions to gauge emotional stress. The onboard computer has an animated avatar who will try to connect with the patient, armed with tools like colorful animations, happy music, candy scent dispenser, and a bubble-blowing machine.
Continue reading “Hyundai Mini 45 EV Is A Small Car With Grand Ambitions”
Astronomy fans were recently treated to the Great Conjunction, where Jupiter and Saturn appear close together from the perspective of our planet Earth. Astronomy has given us this and many other magnificent sights, but we can get other senses involved. Science News tells of explorations into adapting our sense of hearing into tools of astronomical data analysis.
Data visualization has long been a part of astronomy, but they’re not restricted to charts and graphs that require a trained background to interpret. Every “image” generated using data from radio telescopes (like the recently-lost Arecibo facility) are a visualization of data from outside the visible spectrum. Visualizations also include crowd pleasing false-color images such as The Pillars of Creation published by NASA where interstellar emissions captured by science instruments are remapped to colors in the visible spectrum. The results are equal parts art and science, and can be appreciated from either perspective.
Data sonification is a whole other toolset with different strengths. Our visual system evolved ability to pick out edges and patterns in spatial plots, which we exploit for data visualization. In contrast our aural system evolved ability to process data in the frequency domain, and the challenge is to figure out how to use those abilities to gain scientifically relevant data insight. For now this field of work is more art than science, but it does open another venue for the visually impaired. Some of whom are already active contributors in astronomy and interested in applying their well-developed sense of hearing to their work.
Of course there’s no reason this has to be restricted to astronomy. A few months ago we covered a project for sonification of DNA data. It doesn’t take much to get started, as shown in this student sonification project. We certainly have no shortage of projects that make interesting sounds on this site, perhaps one of them will be the key.
Calculating three-dimensional position from two-dimensional projections are literal textbook examples in geometry, but those examples are the “assume a spherical cow” type of simplifications. Applicable only in an ideal world where the projections are made with mathematically perfect cameras at precisely known locations with infinite resolution. Making things work in the real world is a lot harder. But not only have [Jingtong Li, Jesse Murray et al.] worked through the math of tracking a drone’s 3D flight from 2D video, they’ve released their MultiViewUnsynch software on GitHub so we can all play with it.
Instead of laboratory grade optical instruments, the cameras used in these experiments are available at our local consumer electronics store. A table in their paper Reconstruction of 3D Flight Trajectories from Ad-Hoc Camera Networks (arXiv:2003.04784) listed several Huawei cell phone cameras, a few Sony digital cameras, and a GoPro 3. Video cameras don’t need to be placed in any particular arrangement, because positions are calculated from their video footage. Correlating overlapping footage from dissimilar cameras is a challenge all in itself, since these cameras record at varying framerates ranging from 25 to 59.94 frames per second. Furthermore, these cameras all have rolling shutters, which adds an extra variable as scanlines in a frame are taken at slightly different times. This is not an easy problem.
There is a lot of interest in tracking drone flights, especially those flying where they are not welcome. And not everyone have the budget for high-end equipment or the permission to emit electromagnetic signals. MultiViewUnsynch is not quite there yet, as it tracks a single target and video files were processed afterwards. The eventual goal is to evolve this capability to track multiple targets on live video, and hopefully help reduce frustrating public embarrassments.
[IROS 2020 Presentation video (duration 14:45) requires free registration, available until at least Nov. 25th 2020.]