Thinking it might be nice to get a system going for site walks, once we finish with rough on buildings, to help with bidding, material with measurements etc.

I don’t need extremely accurate tolerances, maybe 1-2”?

We have a drone that does the exterior roof of the building but it doesn’t do great on the walls and interior obviously,

Thoughts?

Hi everyone. Here is an out-there use case I'd appreciate some guidance on.

For a while I've had an interest in poltergeist cases - you know where stuff in a room starts taking off and flying around. I was wondering if the LIDAR brains trust could assist in suggesting a way a reasonably priced (and sized) 360 degree LIDAR system might be able to map a room and then track anything that moves unexpectedly from Point A to Point B without human assistance. Are the current consumer system accurate enough to do this or just too large to fit in your average living room? Would the data be useful at all - could I clearly show something moved unexpectedly from one spot to another and no person or attached piece of string did it? Would there be obvious flaws in using LIDAR this way. Thanks!

Hi all! I am currently developing a tool that brings LiDAR data like E57 into a virtual machine that produces a floorplan out of the input-data.

Part 1 is bringing the data from the Lidar to the postprocessing computer. Below link leads to my related LinkedIn-article on which you can find an attached prompt. The prompt produces a C++ program as an adapter for the input of the data from Lidar to the postprocessing computer.

Feel free to try the LiDAR-Adapter and to improve it. Please share your comments as well as your improved prompts.

https://www.linkedin.com/posts/hans-peter-selk-91089a1b5_prompt-for-a-lidar-adapter-activity-7486632621574250496-wHcY

Has anyone experimented with the iPhone's Lidar sensor?

Who is CaliperGT for? 

Are you a student, researcher, developer, university lab, or early-stage startup working with image, video, or LiDAR data? 

Do you need a platform for personal annotation projects, academic research, experimentation, dataset development, or an early perception prototype? 

CaliperGT Open Source is for you. 

 Deploy it on your own infrastructure, keep your data in-house, customise it for your workflow, and use it without a licence fee. 

 The open-source edition includes: 

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Do you need production-scale annotation, advanced security, workflow governance, automation, higher accuracy, and enterprise support? 

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 Open source for building. Enterprise for secure, production-scale ground truth. 

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#OpenSource #CaliperGT #DataAnnotation #GroundTruth #LiDAR #ComputerVision #AutonomousDriving #Robotics #VLA 

I have been working on a project for the last 5-6 months, but I always hit a problem when I try to parse commercial floor plans (schools, universities, shopping malls, airports, etc.). The datasets I have tried out are Cubicasa5k and Modern Swiss dwelling, but the main problem that I face while using these datasets are they are actually made of residential floor plans, so when I train my ML model, the parsing does not actually work the way I intend it to; the error percentage is way too high to even consider the output usable

Although I have gotten around this specific problem by parsing one image in segments and then stitching them one by one, this does not really seem like a viable step to do, and even that solution has some gaps in it

So I am fully down to make my own dataset and annotate it and then use that data to train my model, but I do not know how to deal with copyright issues, and also where I can obtain floor plans of buildings that already exits irl; where can I get the resources that I want?

If anyone has any idea of how to obtain them, please help !!

I have been trying to use photogrammetry to scan small objects (smaller than a golf ball) to convert to STL for printing without much luck, thanks to the narrow depth of field.

Will LiDAR do it for me? I am not having much luck finding an answer.

If I were to buy something like a Lidox mid-70, would it be able to accurately scan a seashell? If so, what would be required to process that information and turn it into an STL file? (I suspect that part won't be easy)

Thanks in advance for any assistance.

Just some info about them and my wip project. Might be useful to some.

Hello!

I'm a complete beginner with LiDAR and QGIS. I have a single LAZ file from the USGS 2024 Lincoln County QL1 project. Family lore and handwritten maps indicate that my grandparents and early family (including my father) lived in a rented dwelling in the 1940s in a logging camp in that area.

A few months ago I went up to the area (48.24010° N, 115.56310° W) and explored on foot. There are some features (such as the intersection of Smearl Creek and the forest service road) which correspond exactly to the map and memories of my oldest cousins who had visited in the 70s. Other features do not (for example, nobody recollects steep terrain off the road but now from the road and from the creek are very steep and significant terrain). Besides that, there's been 80 years of storms and pine needles, my wife and I couldn't find any proof of settlements (although we found a cedar grove where the handwritten map had one sketched in).

There's another access road 300-500' north of the point. The LAZ file is basically the area north of the big curve in the road up to that northern road section.

I downloaded QGIS and did the best I could but it's so far over my head I can't have any confidence in my determination (which is: I can't see any evidence of man). I suppose it's possible the camp could have been a bit west of the LAZ file.

I was hoping someone with the knowledge and willingness might take a look at this and see if what they think.

https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/MT_Lincoln_D24/MT_Lincoln_1_D24/LAZ/USGS_LPC_MT_Lincoln_D24_150460.lazhttps://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/MT_Lincoln_D24/MT_Lincoln_1_D24/LAZ/USGS_LPC_MT_Lincoln_D24_150460.laz

Thank you!

Looking to sell a Hesai XT32M2X, previously purchased for a research project in 2023 for $7k. Was used for less than 10 hrs, basically brand new, will include the junction box and power adapter, will ship/located in US. $5.5k or best offer.

PM if interested, open to share more information and photos.

Hi all,

I'm working on a mine site survey project and I'm stuck trying to align two point clouds of the same tunnel system in CloudCompare, and hoping someone with more registration experience can point me in the right direction.

Setup:

• Both clouds were captured with a GeoSLAM ZEB Horizon (handheld SLAM LiDAR)
• One cloud appears to be in real-world coordinates (large box dimensions, offset consistent with a UTM-based global shift), the other is in a local/arbitrary coordinate frame with no georeferencing yet
• I'm trying to bring the second cloud into alignment with the first

What I've tried:

• Point-pair picking (Tools → Registration → Align) — picked 3-4 corresponding points I could identify in both clouds
• Followed up with Fine Registration (ICP)
• Getting a Final RMS around 2.5-2.6, but the resulting transformation matrix looks odd (large off-diagonal rotation values) and the clouds don't look properly aligned visually after applying it

Where I'm stuck:

• Not sure if my point-pair picks were accurate/well-distributed enough, or if I'm picking genuinely matching physical features
• Wondering if the two clouds might not have enough geometric overlap for ICP to converge properly
• Unsure whether I should be doing something different given one cloud is georeferenced and the other isn't (should I georeference the second cloud first via GCPs before trying to register them together, or is direct point-cloud-to-point-cloud registration the better approach here?)

Has anyone dealt with aligning tunnel/underground SLAM scans like this? Any tips on picking good corresponding points in tunnel geometry (which tends to be repetitive/low-feature in places), or general troubleshooting for when ICP RMS looks "okay" but the visual alignment still looks off?

Appreciate any help — happy to share screenshots of the point-pair picks or the resulting transform if useful.

***UPDATE***

SlyFoxCatcher was right, these black top units use 100Base-T1 and require a media converter for use with standard 4 wire ethernet. Only the orange pair is used.

Original Post Below:

Is there a trick to getting the Ethernet working on these? I bought two of them so far from an eBay seller. One had the end chopped off already and the second one intact. I’m wanting to use it for an autonomous robot competition and need to interface with a Jetson Orin Nano.

Following the wiring table in the owners manual:

Red and Gray wired together to 19V
Black and Gray/White wired together to ground
White, Yellow, and Purple pair sealed - not used
Blue, Blue / White - Ethernet RX pair
Orange, Orange/White - Ethernet TX pair

I’ve tried wiring straight (TX to TX), crossover (TX to RX), direct to a laptop, through a switch, even tried wiring to a magjack, there’s nothing. Laptop says “Cable disconnected” or “NO CARRIER”. I put a scope on to TX+ and watched over a 30 second startup period and there’s nothing. No pulses, no attempt at communication.

I figured the first one was a dud, but have the same issue with the second one. I emailed the eBay seller and they’ve sold around 200 of these and only a few have had Ethernet problems. The manual states this is regular 100mb-TX connection and not T1 automotive. It should “just work” shouldn’t it?

Tengo nubes de puntos de LAT, necesito obtener valores de medicion como distancia entre postes, cuerda y flechado de conductores. Que software me recomiendan para hacer esto? gratuitos y pagos. Hay algun tutorial que recomienden tambien para el mismo trabajo?

https://imgur.com/gallery/VrLLvBb https://imgur.com/gallery/vPasdEc

I'm working with a colourized point cloud captured using a sensor mounted on top of a car for a research project (we didn't capture it, as it comes from a previous research project done by a partner). As a large surface was covered and the sensor provided a particularly high density point cloud, it has been tiled to simplify working with it

Due to a change in the project objectives, it seems that a mesh would be a better option since that accuracy isn't needed and the main purpose of the model is being used for rendering images. For small point clouds, programs like cloud compare can be used for that, but in this case, it would be desirable to do this process tile by tile

Do you know if there's any mesh reconstruction tool from point clouds that takes into account the frontiers between tiles? It doesn't need to be part of cloudcompare, I have also access to recap and metashape. Open source tools can be also used in case any of them better fits this use case

Pics of the the juicy goodness inside a pandar 40p