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andrewda avatar andrewda commented on June 15, 2024

Same here. The highest number of samples I can get reach before the map stops being built is 120, even on my Jetson TX1 which is surprising as I'd expect it to be able to handle stuff like this. What's more, the CPU never goes above ~50% while generating the map, so I'm not sure where the bottleneck could be. I can delve more into system information and setup when I get home in a few hours.

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simondlevy avatar simondlevy commented on June 15, 2024

Yeah, I and others have had a some difficulty using these RP Lidar units with BreezySLAM, having to tune that min-samples parameter. I'm not sure whether the solution lies in re-writing the acquisition library or the core C in BreezySLAM. Given how fast BreezySLAM already runs on even inexpensive single-board computers like ODROID using other lidar units (like the Hokuyo URGs), my approach would be to try and speed up the RP Lidar acquisiton code.

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andrewda avatar andrewda commented on June 15, 2024

Alright, that makes sense. I'll look into making my own acquisition library in something faster than Python. Thanks!

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titusece avatar titusece commented on June 15, 2024

Hello,
Any further update on this issue ?
I am unable to get map bytes for my RPILIDAR A1, it just returns 0x7F data.
slam.getmap(mapbytes)

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kenkyusha avatar kenkyusha commented on June 15, 2024

Using the C++ is much better and you get much more points! Haven't tested the slam yet but I would guess it is good (looking at the offline data and map generation)

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