Tag Archives: pretty
#439555 Unitree’s Go1 Robot Dog Looks Pretty ...
In 2017, we first wrote about the Chinese startup Unitree Robotics, which had the goal of “making legged robots as popular and affordable as smartphones and drones.” Relative to the cost of other quadrupedal robots (like Boston Dynamics’ $74,000 Spot), Unitree’s quadrupeds are very affordable, with their A1 costing under $10,000 when it became available in 2020. This hasn’t quite reached the point of consumer electronics that Unitree is aiming for, but they’ve just gotten a lot closer: now available is the Unitree Go1, a totally decent looking small size quadruped that can be yours for an astonishingly low $2700.
Not bad, right? Speedy, good looking gait, robust, and a nifty combination of autonomous human following and obstacle avoidance. As with any product video, it’s important to take everything you see here with a grain of salt, but based on Unitree’s track record we have no particular reason to suspect that there’s much in the way of video trickery going on.
There are three versions of the Go1: the $2700 base model Go1 Air, the $3500 Go1, and the $8500 Go1 Edu. This looks to be the sort of Goldilocks pricing model, where most people are likely to spring for the middle version Go1, which includes better sensing and compute as well as 50% more battery life an an extra m/s of speed (up to 3.5m/s) for a modest premium in cost. The top of the line Edu model offers higher end computing, 2kg more payload (up to 5kg), as well as foot-force sensors, lidar, and a hardware extension interface and API access. More detailed specs are here, although if you’re someone who actually cares about detailed robot specs, what you’ll find on Unitree’s website at the moment will probably be a little bit disappointing.
We’ve reached out to Unitree to ask them about some of the specs that aren’t directly addressed on the website. Battery life is a big question—the video seems to suggest that the Go1 is capable of a three-kilometer, 20-minute jog, and then some grocery shopping and a picnic, all while doing obstacle avoidance and person following and with an occasional payload. If all of that is without any battery swaps, that’s pretty good. We’re also wondering exactly what the “Super Sensory System” is, what kinds of tracking and obstacle avoidance and map making skills the Go1 has, and exactly what capabilities you’ll be required to spring for the fancier (and more expensive) versions of the Go1 to enjoy.
Honestly, though, we’re not sure what Unitree could realistically tell us about the Go1 where we’d be like, “hmm okay maybe this isn’t that great of a deal after all.” Of course the real test will be when some non-Unitree folks get a hold of a Go1 to see what it can actually do (Unitree, please contact me for my mailing address), but even at $3500 for the midrange model, this seems like an impressively cost effective little robot.
Update: we contacted Unitree for more details, and they’ve also updated the Go1 website to include the following:
The battery life of the robot while jogging is about 1 hour
It weighs 12kg
The Super Sensory System includes five wide-angle stereo depth cameras, hypersonic distance sensors, and an integrated processing system
It’s running at 16 core CPU and a 1.5 tflop GPU
We also asked Wang Xingxing, Unitree’s CEO, about how they were able to make Go1 so affordable, and here’s what he told us:
Unitree Go1 can be regarded as a product that we have achieved after 6-7 years of iteration at the hardware level, only to achieve the goals of ultra-low cost, high reliability and high performance. Our company actually spent more manpower and money than software on the hardware level such as machinery. Continue reading
#439294 Unitree’s Go1 Robot Dog Looks Pretty ...
In 2017, we first wrote about the Chinese startup Unitree Robotics, which had the goal of “making legged robots as popular and affordable as smartphones and drones.” Relative to the cost of other quadrupedal robots (like Boston Dynamics’ $74,000 Spot), Unitree’s quadrupeds are very affordable, with their A1 costing under $10,000 when it became available in 2020. This hasn’t quite reached the point of consumer electronics that Unitree is aiming for, but they’ve just gotten a lot closer: now available is the Unitree Go1, a totally decent looking small size quadruped that can be yours for an astonishingly low $2700.
Not bad, right? Speedy, good looking gait, robust, and a nifty combination of autonomous human following and obstacle avoidance. As with any product video, it’s important to take everything you see here with a grain of salt, but based on Unitree’s track record we have no particular reason to suspect that there’s much in the way of video trickery going on.
There are three versions of the Go1: the $2700 base model Go1 Air, the $3500 Go1, and the $8500 Go1 Edu. This looks to be the sort of Goldilocks pricing model, where most people are likely to spring for the middle version Go1, which includes better sensing and compute as well as 50% more battery life an an extra m/s of speed (up to 3.5m/s) for a modest premium in cost. The top of the line Edu model offers higher end computing, 2kg more payload (up to 5kg), as well as foot-force sensors, lidar, and a hardware extension interface and API access. More detailed specs are here, although if you’re someone who actually cares about detailed robot specs, what you’ll find on Unitree’s website at the moment will probably be a little bit disappointing.
We’ve reached out to Unitree to ask them about some of the specs that aren’t directly addressed on the website. Battery life is a big question—the video seems to suggest that the Go1 is capable of a three-kilometer, 20-minute jog, and then some grocery shopping and a picnic, all while doing obstacle avoidance and person following and with an occasional payload. If all of that is without any battery swaps, that’s pretty good. We’re also wondering exactly what the “Super Sensory System” is, what kinds of tracking and obstacle avoidance and map making skills the Go1 has, and exactly what capabilities you’ll be required to spring for the fancier (and more expensive) versions of the Go1 to enjoy.
Honestly, though, we’re not sure what Unitree could realistically tell us about the Go1 where we’d be like, “hmm okay maybe this isn’t that great of a deal after all.” Of course the real test will be when some non-Unitree folks get a hold of a Go1 to see what it can actually do (Unitree, please contact me for my mailing address), but even at $3500 for the midrange model, this seems like an impressively cost effective little robot. Continue reading
#439105 This Robot Taught Itself to Walk in a ...
Recently, in a Berkeley lab, a robot called Cassie taught itself to walk, a little like a toddler might. Through trial and error, it learned to move in a simulated world. Then its handlers sent it strolling through a minefield of real-world tests to see how it’d fare.
And, as it turns out, it fared pretty damn well. With no further fine-tuning, the robot—which is basically just a pair of legs—was able to walk in all directions, squat down while walking, right itself when pushed off balance, and adjust to different kinds of surfaces.
It’s the first time a machine learning approach known as reinforcement learning has been so successfully applied in two-legged robots.
This likely isn’t the first robot video you’ve seen, nor the most polished.
For years, the internet has been enthralled by videos of robots doing far more than walking and regaining their balance. All that is table stakes these days. Boston Dynamics, the heavyweight champ of robot videos, regularly releases mind-blowing footage of robots doing parkour, back flips, and complex dance routines. At times, it can seem the world of iRobot is just around the corner.
This sense of awe is well-earned. Boston Dynamics is one of the world’s top makers of advanced robots.
But they still have to meticulously hand program and choreograph the movements of the robots in their videos. This is a powerful approach, and the Boston Dynamics team has done incredible things with it.
In real-world situations, however, robots need to be robust and resilient. They need to regularly deal with the unexpected, and no amount of choreography will do. Which is how, it’s hoped, machine learning can help.
Reinforcement learning has been most famously exploited by Alphabet’s DeepMind to train algorithms that thrash humans at some the most difficult games. Simplistically, it’s modeled on the way we learn. Touch the stove, get burned, don’t touch the damn thing again; say please, get a jelly bean, politely ask for another.
In Cassie’s case, the Berkeley team used reinforcement learning to train an algorithm to walk in a simulation. It’s not the first AI to learn to walk in this manner. But going from simulation to the real world doesn’t always translate.
Subtle differences between the two can (literally) trip up a fledgling robot as it tries out its sim skills for the first time.
To overcome this challenge, the researchers used two simulations instead of one. The first simulation, an open source training environment called MuJoCo, was where the algorithm drew upon a large library of possible movements and, through trial and error, learned to apply them. The second simulation, called Matlab SimMechanics, served as a low-stakes testing ground that more precisely matched real-world conditions.
Once the algorithm was good enough, it graduated to Cassie.
And amazingly, it didn’t need further polishing. Said another way, when it was born into the physical world—it knew how to walk just fine. In addition, it was also quite robust. The researchers write that two motors in Cassie’s knee malfunctioned during the experiment, but the robot was able to adjust and keep on trucking.
Other labs have been hard at work applying machine learning to robotics.
Last year Google used reinforcement learning to train a (simpler) four-legged robot. And OpenAI has used it with robotic arms. Boston Dynamics, too, will likely explore ways to augment their robots with machine learning. New approaches—like this one aimed at training multi-skilled robots or this one offering continuous learning beyond training—may also move the dial. It’s early yet, however, and there’s no telling when machine learning will exceed more traditional methods.
And in the meantime, Boston Dynamics bots are testing the commercial waters.
Still, robotics researchers, who were not part of the Berkeley team, think the approach is promising. Edward Johns, head of Imperial College London’s Robot Learning Lab, told MIT Technology Review, “This is one of the most successful examples I have seen.”
The Berkeley team hopes to build on that success by trying out “more dynamic and agile behaviors.” So, might a self-taught parkour-Cassie be headed our way? We’ll see.
Image Credit: University of California Berkeley Hybrid Robotics via YouTube Continue reading