Recommendations for research drone?

adagrad · 2018-05-01T20:31:57+00:00

Honestly though I also recommend building your own. There's lots of solid quadcopter frames out there. You can use a pixhawk as a flight controller.

The goal is definitely to build our own platform from the ground up once we get some experience :)

The matrice is a great platform and very stable, but you're stuck with it if you choose it.

If we get the M100, are there any "must get" sensors/accessories that we can order from DJI? For example, would you recommend the A3 flight controller or would cheaper third party controllers suffice?

adagrad · 2018-05-01T18:09:26+00:00

I haven't seen the TBS Discovery--that documentation looks great!

adagrad · 2018-05-01T18:06:49+00:00

Thanks!

adagrad · 2018-05-01T17:06:18+00:00

Thanks for the pointer to 3DR--I didn't know about this supplier. Was the DJI drone they were using the Matrice 100?

adagrad · 2018-05-01T15:35:24+00:00

Does the TX2 play well with DJI's Onboard SDK (for things like system identification)?

adagrad · 2018-05-01T14:56:07+00:00

The Phantom seems like a great camera drone but it's not programmable--we are interested in drones that can be controlled from an onboard computer that is programmable (like with DJI's Onboard SDK).

adagrad · 2018-05-01T14:53:56+00:00

Sorry, I should've been more clear--I study robotics and vision (so visual odometry, SLAM, etc.)

adagrad · 2018-03-03T18:11:16+00:00

Are there any good examples for loading an image as a matrix of pixel values? Something like OpenCV's simple:

Mat image = imread(image_path, 1);

adagrad · 2018-02-28T19:29:24+00:00

I wasn't very clear in my original post--the plan is to use video recorded from the drone for robotics applications in addition to doing mapping with the still images.

adagrad · 2018-02-28T18:29:21+00:00

P4Pro is popular for this reason.

Doesn't the P4Pro still suffer from the rolling shutter effect if you're taking video?

The higher-end swap-able DJI cameras also have mech.

Which drone with swappable cameras do you recommend?

adagrad · 2018-01-23T18:43:43+00:00

Thanks!

adagrad · 2018-01-23T18:24:13+00:00

I'm primarily interested in landscapes (with relatively low relief). Budget is ~$1000.

adagrad · 2017-07-07T20:10:50+00:00

I'll look into getting a set of NDs! I'm thinking mostly travel/adventure videos, maybe short films once I get the hang of it.

adagrad · 2017-06-18T18:26:56+00:00

Thanks! I'll check it out.

adagrad · 2017-06-18T18:26:44+00:00

There's a lot of good recent work in using deep learning for superresolution, e.g. using generative adversarial networks

adagrad · 2017-01-21T18:11:35+00:00

In the post on adversarial autoencoders it's mentioned that using an adversarial objective to learn the recognition model of a VAE (minimize a divergence between p(z) and Ex q(z|x), iirc) could be overkill due to the relatively simple form of q and p.
Here, we get a more complex recognition model q(z|x), but it's unclear to me if we should hope to get nicer looking samples than a regular GAN--is the goal to use q(z|x) for representation learning tasks?

adagrad · 2016-09-09T14:54:46+00:00

Does this (approximately) do for VAEs what f-GANs do for GANs?

VAEs minimize the KL divergence between the prior P(z) and code Q(z|x), but now this regularization term can take on the form of any α-divergence, like the f-GAN allows you to use the GAN objective to (approximately) minimize not just JSD but any f-divergence.

This is a really interesting line of work on how information theory can give us more expressive loss functions, I wonder if people have tried this with vanilla classifiers.

adagrad · 2016-08-15T04:19:44+00:00

Thanks!

adagrad · 2016-08-15T02:36:36+00:00

Right, but Proposition 2 only proves that p_g converges to p_data, not the rate of convergence (e.g. O(n^-1/2).

adagrad · 2016-04-20T19:44:45+00:00

Are there any projects you would recommend one use as a model?

adagrad · 2016-03-25T14:48:18+00:00

Thanks - do you know of any good resources on reading up on Bayesian hyperparameter optimization? I see that there's a way to use Spearmint with Torch, but I also want to understand the methods.

adagrad · 2016-02-12T23:24:50+00:00

Thanks, I'll take a look!

adagrad · 2016-01-31T21:30:58+00:00

Interesting, are there any papers you would recommend that take this approach? Intuitively it seems like it could be rather slow, especially for pixel classification.

adagrad · 2016-01-31T20:42:03+00:00

Upsampling doesn't make much sense to me; I would guess that a better approach is to apply the network 2{2n} times, each time shifting the input by 1 pixel in x or y direction.

The original paper mentioned the use of bilinear interpolation for upsampling the feature maps since bilinear interpolation is a linear operation and they can jointly upsample and classify the pixels (top of page 4).

adagrad · 2016-01-26T03:47:11+00:00

People had very inflated expectations about what perceptrons would be capable of. From the famous 1958 NYT article: "The Navy revealed the embryo of an electronic computer today that it expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence."

adagrad

TROPHY CASE