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Occupancy Grid - beginner

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jwatte:

--- Quote ---the path will be a list of cells
--- End quote ---

If the size of a cell is 50x50 cm, then the admissibility criteria for a cell in the path should be that every neighboring cell is not blocked. This will effectively achieve making a "safety margin" in the way that you describe, except it will do it when searching, rather than when storing the data. Storing the safety margin in the grid is less optimal because it doesn't allow you to run different kinds of searches on the same grid, and it also makes it harder to tell whether a "blocked" cell is blocked because of safety margin, or because of an actual reading.

In general, path planning is a well solved problem assuming you have the map; you should go read some textbooks on the subject. Note that space for the robot to turn may also be needed -- part of the "search space" would be to include turning/re-orientation sequences.

Finally, to track objects on an object basis rather than a grid basis, go look at research papers in the subject. That's pretty much state of the art. I imagine CiteSeerX or Google Scholar would have a good index. citeseerx.ist.psu.edu

activex:

--- Quote --- Storing the safety margin in the grid is less optimal because it doesn't allow you to run different kinds of searches on the same grid
--- End quote ---

If I make a Clone() of this Map and dealt with the safety margin in the cloned map, what you think?

jwatte:
That might work, but it's still an inelegant way of doing it IMO. Compensating for limitations in the admissibility test is the more elegant and "right" way to do it in my experience.

beautifulsmall:
The problem of the chair legs !
a probability map
Generated over several days to determine the probability of an object location.

The data must be in such a format that it can be used to create paths of varying likley sucess's.  A wonderful problem . the filter time can be self adjusting to the object frequency, Im talikng myself into kalman on each leg.

I think the chair legs is a nice model as it has multiple fixed similar objects which a small domestic robot would need to manouver between. THey are fixed to each other but random in the room.

I m also unsure if the data needs to be aligned to real world map, dont use wheel odometry. Use a high rate distance ranging method to measure distance and acceleration.
Im now trying to build a 1Khz sample laser tof for under $150.

With the sensors you have you should be able to move at half the max sensor range distance in the sample time if you go from a standing start and your accel is the same as your brake. No accel over 1G for wheel based standard vehicles.

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