Suzhou2

Learning to Walk

Video of experimental setup.
Experimental Setup

(11.0 MB MPEG)

To learn to walk faster, the Aibos evaluated different gaits by walking back and forth across the field between pairs of beacons, timing how long each lap took. The learning was all done on the physical robots with no human intervention (other than to change the batteries). To speed up the process, we had three Aibos working simultaneously, dividing up the search space accordingly.

Video of initial gait.
Initial Gait

(2.8 MB MPEG)

Initially, the Aibo's gait is clumsy and fairly slow (less than 150 mm/s). We deliberately started with a poor gait so that the learning process would not be systematically biased towards our best hand-tuned gait, which might have been locally optimal.

Midway through the training process, the Aibo is moving much faster than it was initially. However, it still exhibits some irregularities that slow it down.

Video of the training process.
Training Process

(1.7 MB MPEG)

After traversing the field a total of just over 1000 times over the course of 3 hours, we achieved our best learned gait, which allows the Aibo to move at approximately 291 mm/s. To our knowledge, this is the fastest reported walk on an Aibo as of November 2003. The hash marks on the field are 200 mm apart. The Aibo traverses 9 of them in 6.13 seconds demonstrating a speed of 1800mm/6.13s > 291 mm/s.

Achieving a fast walk is an essential part of being a competitive team. At competitions, if needed, we re-train our walk for the specific playing surface of the venue. Because the robots train with minimal human involvement, team members can work on other things in that time.

Side view of best learned gait.
Fastest Gait: Side View

(1.4 MB MPEG)
Front view of the fastest gait.
Fastest Gait: Front View

(2.3 MB MPEG)
Another side view of the walk.
Fastest Gait: Side View 2

(1.7 MB MPEG)
Initial gait for the ERS-7
Initial gait for ERS-7
(0.9 MB AVI)
(0.3 MB MP4)
Learned gait for the ERS-7
Faster learned gait for ERS-7
(0.7 MB AVI)
(0.3 MB MP4)

A fast gait is an essential component of any successful team in the RoboCup 4-legged league. However, quickly moving quadruped robots, including those with learned gaits, often move in such a way so as to cause unsteady camera motions which degrade the robot's visual capabilities. One direction that we have continued this research in is by searching for a parameterized walk while optimizing for both speed and stability.

To the best of our knowledge, previous learned walks have all focused exclusively on speed. Our method is fully implemented and tested on the Sony Aibo ERS-7 robot platform. The resulting gait is reasonably fast and considerably more stable compared to our previous fast gaits. We demonstrate that this stability can significantly improve the robot's visual object recognition.

A gait optimized only for speed.
A gait optimized only for speed

(4.1 MB MPEG)
A gait optimized only for speed.
A gait optimized only for both speed and stability

(4.1 MB MPEG)

Full details of our approach are available in the following papers:

Valid CSS!
Valid XHTML 1.0!