Well, to address the title of the article, robot motion usually doesn't look very good for a known reason. The motion control systems used are usually positional. Most robotic control systems have a processor or PLC for each joint, and that processor usually accepts position goals, not force goals. Then there's some central coordinator issuing positional commands. This is simple to code, and many robotics frameworks have that hierarchical approach more or less nailed into them.
That hierarchical approach is not very good for dynamic motion. For that, you need force control and coordination in force space. I used to work on this; here's the first anti-slip control for legged robots, from 1995: (https://www.youtube.com/watch?v=kc5n0iTw-NU). That was picked up by a grad student at McGill, who put it into their running quadruped Scout II. Then his professor, Martin Buehler, left McGill for Boston Dynamics and became the head engineer on BigDog.
All the actuators on BigDog are run by one CPU, which is a Pentium 4 class machine running QNX. The balance servoloop runs at 100Hz, and the hydraulic valve control loop runs at 1KHz. This allows for coordinated force control across all actuators, which is why BigDog is so agile. The Atlas robot version 1 is basically a modified BigDog, although version 2 seems to have been redesigned above the hips, with onboard power.
The motion in the DARPA Humanoid Challenge looked so bad last time because most of the participants using the Atlas robot were using a Windows DLL provided by Boston Dynamics. That DLL was just intended to provide some basic functionality to get participants started. Functions provided included "walk slowly" and "stand stably while arms do something". They didn't have the running, balance recovery, or slip control capabilities Boston Dynamics put into Big Dog. Expect much better performance in round 2 next winter.
Until recently, most robotics simulators were hopeless about force accuracy or friction. Most of them used physics engines borrowed from video game technology, where nobody cares about force accuracy or friction as long as things blow up prettily. This was recognized as a problem by DARPA, and they funded Dr. Mike Sherman at Stanford to put a serious dynamics simulator into Gazebo. Sherman previously had a commercial company, Symbolic Dynamics, building dynamics simulators for industry, and did know how to get the dynamics right. So now you can simulate force-controlled robots in Gazebo.
(Unfortunately, it took two decades to get this right, so I've moved on to other things, after a detour through physics engines for animation.)
Anyway, that's why robots can't dance very well yet. That problem is being fixed.
That hierarchical approach is not very good for dynamic motion. For that, you need force control and coordination in force space. I used to work on this; here's the first anti-slip control for legged robots, from 1995: (https://www.youtube.com/watch?v=kc5n0iTw-NU). That was picked up by a grad student at McGill, who put it into their running quadruped Scout II. Then his professor, Martin Buehler, left McGill for Boston Dynamics and became the head engineer on BigDog.
All the actuators on BigDog are run by one CPU, which is a Pentium 4 class machine running QNX. The balance servoloop runs at 100Hz, and the hydraulic valve control loop runs at 1KHz. This allows for coordinated force control across all actuators, which is why BigDog is so agile. The Atlas robot version 1 is basically a modified BigDog, although version 2 seems to have been redesigned above the hips, with onboard power.
The motion in the DARPA Humanoid Challenge looked so bad last time because most of the participants using the Atlas robot were using a Windows DLL provided by Boston Dynamics. That DLL was just intended to provide some basic functionality to get participants started. Functions provided included "walk slowly" and "stand stably while arms do something". They didn't have the running, balance recovery, or slip control capabilities Boston Dynamics put into Big Dog. Expect much better performance in round 2 next winter.
Until recently, most robotics simulators were hopeless about force accuracy or friction. Most of them used physics engines borrowed from video game technology, where nobody cares about force accuracy or friction as long as things blow up prettily. This was recognized as a problem by DARPA, and they funded Dr. Mike Sherman at Stanford to put a serious dynamics simulator into Gazebo. Sherman previously had a commercial company, Symbolic Dynamics, building dynamics simulators for industry, and did know how to get the dynamics right. So now you can simulate force-controlled robots in Gazebo.
(Unfortunately, it took two decades to get this right, so I've moved on to other things, after a detour through physics engines for animation.)
Anyway, that's why robots can't dance very well yet. That problem is being fixed.