Spirit Rover Makes Longest Trip Yet
ivan1011001 writes "Spirit traveled just over 88 feet in an attempt to visit the crater "Bonneville" to look for evidence of water on Mars. Engineers had hoped the rover would travel 164 feet, but Spirit didn't cover the full distance because it spent more time than initially planned studying rocks and soil along the way. This is longer than its earlier PR of 70 feet."
(Time And)Relative Dimensions in space... for the uninformed :-)
:-)
Anyone else think it's sort of funny that you have a probe that travels millions of miles to another planet, and the news is that it's then travelled a further 88 feet
Simon.
Physicists get Hadrons!
Didn't the Soviet built lunar rovers go much further in a single day back in the early 70's? What sort of over-hyped/overly-specific record is this?
"And the award for longest roving in the past 3 weeks on a neighboring planet by an American robot who's name rhymes with 'kirit' goes to...."
I demand a recount!
"If you want to improve, be content to be thought foolish and stupid." - Epictetus
I don't think it was artificial curiosity - Mission Control gave it instructions to the effect of: "study these rocks, then move towards the crater". They thought it would take x minutes to study the rocks, leaving enough time to travel 164 feet, but instead it took 2x minutes, and the rover only had enough time left to travel 88 feet.
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I think it is a combination of the two...
Mission control sends a command like:
"Go to Rock A"
"Extend Arm, place payload element X on Rock"
"Let Payload element X analyze rock A"
"Switch to Payload Element Y"
"Let Payload Element Y Analyze Rock A"
(...repeat for each element Mission control wants to use...)
"Stow Arm"
"Navigate at bearing of 110deg until Z time"
Each of the science payloads may take an unknown amount of time to perform it's task - the rock grinder probably moves at different speeds based on the density of the rock.
Also, the driving algorythm probably takes more time to analyze no-so-good paths than good paths.
Sticks and Stones may break my bones, but copyright will always protect me.
Anyone who has tried to go for a walk with a 2 or 3 year old kid knows what I'm talking about. You want to walk, but the annoying little brat will stop and examine very carefully every piece of litter, little stone, gravel or mark on the floor. Half way through the whole thing you'll get tired and just go home.
Exploring that piece of litter, stone, gravel, mark on the floor is the whole point of the walk for a little kid. Ditto for the Mars rovers. Our concepts of what a walk should be like do not apply - there is no predetermined itinerary that must be covered, only wide open eyes that want to understand all the marvels that they see.
Be faithful to your obsessions. Identify them and be faithful to them, let them guide you like a sleepwalker. JG Ballard
Well, that seems to be the 'common' understanding of AI, but in the computer science (and other scientific fields), it has a more specific meaning. Otherwise, factoring large numbers would also be considered AI, although there is nothing intelligent about it, given a good algorithm. Finding that algorithm is what would require intelligence.
Here is a definition I like:
AI is the capacity of a digital computer or computer-controlled robot device to perform tasks commonly associated with the higher intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. The term is also frequently applied to that branch of computer science concerned with the development of systems endowed with such capabilities. --- Herbert A. Simon, Professor of Computer Science and Psychology, Carnegie Mellon University
I am nitpicking here, but given an algorithm to extract edges and corners from two images, using the camera calibration values to calculate distance, and creating a map based on these data does not require intelligence, and as such isn't strictly AI.
The robot still follows strict instructions which find the optimal path. It will not learn if this algorithm fails a certain number of times, it will not generalise to make future computation quicker, like a human would. It does not have a concept of the obstacles. It does not get more proficient after doing the same for a while. So, even though it's a brilliant example of applied computer vision and autonomous navigation, there is very little of what is considered AI involved. Hope this clears it up a bit.