six were ever meaningful) was that I could process multiple hits at once.
With two eyes, had the accuracy been ok, then the distance was sufficient to
allow a positive fix in 2D space by using a bit of geometry (keep in mind, I
had two computers receiving and processing sensor data, so processing power
wasn't an issue). This would take care of the wide cone issue, unless both
sensors got echoes off of different things that were at about the same
distance, but off to different sides. This scenario, too, could be handled,
as all echoes would be written to a DB, and another process would be
studying the echoes and putting them into objects. Under that scenario,
three to five objects would provide a pretty good fix, even in transit.
A narrow cone on a pivot is a viable alternative, but a whole different
concept, so I'll have to think about that.
dan michaels wrote:
>
>
> Actually, I don't think I would try to do this with SRF0x units. They
> have wide beams, and how will you ever know that any 2 echos are from
> the same object?
>
> I think you'd do better with some kind of narrow beam device, which
> you could pan on a servo, in order to localize objects. Eg, the Sharp
> sensors have very narrow beams, and you could correlate the readings
> with the sonar distance readings. Also, some of the newer Maxsonars
> are supposed to have narrower beams.
>
> I also don't see the point of having 17 echo returns, as IIRC, they
> are all from objects at different distances with the SRF0x, and you
> seem to want to ID a specific object.
>
> What I would do is mount a couple of different types of sensor,
> narrow- and wide-field, on the servo, and pan the array, and then
> cross-correlate the results for consistency. I might even use a CdS
> cell with a tube on the front to narrow the FOV, as most objects will
> have a different reflectance than the background or nearby objects.
>
> If you read Joe Jones' book, Robot Programming, he spends a lot of
> time talking about how sensor readings are generally unreliable, and
> you need a lot of cross-comparison capability.
>
>
>
--
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