u/keyable

https://preview.redd.it/kcjo1yxeqvzg1.png?width=727&format=png&auto=webp&s=5bfb1bc1d0e2b953d6687a03bb21ed4474aae200

I’m honestly a bit lost with the number of AI chatbots available these days. There are so many options and very mixed opinions, so it’s hard to figure out what actually works in real, everyday use.

I’d really appreciate hearing from people who actively use these tools in a similar field.

My situation is pretty specific: I want to commit to one AI assistant (paid plan) and use it as a daily tool for engineering work. My main focus is:

Power engineering (hydropower, solar, wind design)

Land surveying (GNSS receivers, drones)

Working with Autodesk software (AutoCAD, Civil 3D, etc.)

So I’m not looking for something just for casual use — I need something reliable for technical questions, problem-solving, and practical engineering support.

From what I’ve seen so far, tools like ChatGPT, Claude, Google Gemini, and Perplexity AI all have their strengths, but it’s not clear which one is best when you actually rely on it daily.

For example:

Some say Claude is better for deep reasoning and coding

Others prefer ChatGPT for versatility and tools

Gemini seems strong with Google integration and live data

Perplexity looks good for research with sources

But I’d really like to hear real-world experience, especially from engineers or technical users.

If you had to choose just one AI to subscribe to and use heavily, which would you pick and why?

Thanks in advance 🙌

I am planning a long corridor LiDAR survey mission using the DJI Matrice 400 equipped with the L3 payload. The project consists of two segments: the first approximately 3 km in length and the second approximately 15 km. I intend to use the corridor planning functionality available in DJI Pilot 2 and would appreciate guidance on optimizing the mission design, particularly with respect to LiDAR calibration.

I have several specific questions:

1. Would it be acceptable to execute the mission using a single centerline (one-way) flight path?
2. Alternatively, is it preferable to conduct a back-and-forth (bidirectional) flight pattern without including a centerline pass?
3. (Clarification) In the case of a back-and-forth approach, is there any benefit to excluding the centerline entirely, or should it still be incorporated?
4. From a calibration and data quality perspective, would it be advisable to divide the corridor into smaller segments (e.g., 1 km sections), executing separate missions sequentially? This would allow the LiDAR system to perform IMU calibration at the start of each segment.

My concern primarily relates to LiDAR calibration behavior. When initiating a mission, the system performs IMU calibration; however, during a long continuous mission, calibration occurs only at the beginning (and possibly at the end). For example, in a 5 km back-and-forth mission, calibration would not be repeated during intermediate flight segments. I am uncertain whether this could negatively impact data accuracy over longer distances.

Conversely, splitting the mission into multiple shorter segments would ensure more frequent calibration cycles, but at the cost of reduced operational efficiency and increased total flight time.

I would appreciate any recommendations on balancing calibration integrity with operational efficiency for long corridor LiDAR missions.

Thank you.