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- Path: sparky!uunet!snorkelwacker.mit.edu!ai-lab!aztec!bleck
- From: bleck@aztec.ai.mit.edu (Olaf Bleck)
- Newsgroups: comp.robotics
- Subject: Re: Cheap, light orientation sensor needed
- Date: 10 Nov 1992 02:51:58 GMT
- Organization: MIT Artificial Intelligence Laboratory
- Lines: 25
- Sender: bleck@aztec (Olaf Bleck)
- Distribution: world
- Message-ID: <1dn84eINN8m9@life.ai.mit.edu>
- References: <1sDsTB1w165w@galsci.uucp> <1992Nov6.165554.16576@PacBell.COM>
- Reply-To: bleck@ai.mit.edu
- NNTP-Posting-Host: aztec.ai.mit.edu
-
- In article <1992Nov6.165554.16576@PacBell.COM>, tlhouns@ns.pacbell.com (Lee Hounshell) writes:
- |> I had an idea for constructing one using "bend" sensors with weights attached
- |> to one end. As the robot's orientation would change, the sensors would move
- |> (because of gravity pulling the weights). If several of these sensors were
- |> placed strategically inside a robot's chassis, I suspect that one could calculate
- |> the robot's orientation fairly accurately. Any comments?
-
-
- Ah! But wait! What are the weights really telling you? They don't hang
- down with gravity, they hang in the direction of their net acceleration,
- which is the classic problem with "cheap" inertial sensors. Unless your
- robot only samples the sensor when it's been standing still for a while
- (which you need some other sensor to tell you), you don't kow what your
- robot's orientation is, unless you can integrate your sensor perfectly over
- time, and it doesn't have any mechanical error.
-
- This is a particular problem with things like the robotic helicopter task,
- where the helicopter is basically depending in all six axis on inertial data.
- The trend is to use cameras and stuff to look at the ground/horizon/etc. to
- recalibrate a few time/sec.
-
- So you've basically rediscovered inertial nav here, where your "accuracy" is
- basically log($$$)... in the general case.
-
- -Olaf
-