Evolution Robotics' ER1 Reviewed 94
Anonymous Coward writes "A useful review of Evolution Robotics' ER-1 by the boys at Techfocus. It covers: construction, customization, hardware requirements, best features, programming, durability of equipment -- and all that good stuff.
One interesting factoid is that the robot can recognize objects until the object is blocked - up to 40% - by something (like a piece of furniture). Techfocus aptly points out the Orwellian implications... Another thing that rocked my world is the notion that the robot is not as much of a drag on CPU as one might suspect. TF ran the unit on an NEC Versa VXi running Windows 2000, with a 900mhz CPU and 128mb of RAM, and encountered absolutely no problems. Encouragingly, if you want to further customize your robot, why not just write a script in C or Perl -- the manual even points users toward an app primarily based in Linux.
What's not surprising: it's pricey. Also some nice pictures of how the robot really looks right out of the box."
Real world robots (Score:5, Insightful)
Where are they though? I have yet to walk down my street and see a mowing robot or visit a friends house and see a robot cleaning the windows. Most of these articles will say that they will be available to consumers in the next year or so.
Funny, I've been reading articles about robots for what seems like forever
Sensors? (Score:4, Insightful)
How about (Score:1, Insightful)
Especially for topics like this where it doesn't apply even remotely. Name one Orwell book about toy robots.
God, you all are buzzword loving fucktards.
Re:CPU usage depends on tasks (Score:5, Insightful)
I'm sorry but that's a gross simplification. Computer recognition of images, especially images of the real 3D world, is a very hard and computationally intense process. This problem is still at the cutting edge of research. Describing it as "simple processing to compare the input with a matrix of possibilities" is on the same level as describing Doom III as "adds a couple of numbers together and displays some colored dots on the screen". It may be at some level accurate but it misses out the hard parts entirely.
To learn more, you could start at CMU's computer vision [cmu.edu] page. There's a whole world of interesting techniques out there, jump in and try some.