Comments (5)
-
The comment in the Train.ipynb. See answer to (2).
-
The 0.5 in that expression is not 0.5 radians. When testing, I found that the model had a tendency to overcorrect and oversteer. So I added that constant to smooth the output of the model. That should give you an idea of why setting this constant to 0.0009 would cause poor performance. Do note that I would expect that you'd have to retrain the model for Hawaii, which means collecting data for that environment.
-
What do you mean "details"? You can change all of the vehicle model parameters if you download and build AirSim from source. The car asset files are included in the plugin. You'd probably need to recollect data if you change the parameters of the car.
-
You can. It shouldn't have any effect on the modeling, apart from potentially reducing your file size by a bit.
-
You can't without modifying the AirSim source code. To record other views, and more complex scenarios, you can use the python or c++ apis. The build of AirSim that we include with the tutorial is before this feature was introduced.
from autonomousdrivingcookbook.
Thanks! I'll try to built the AirSim by my own with LandscapeMountain.
One last question is the environments (NH,city,Hawaii...etc.) are created by your team?
In marketplace of EPIC GAMES, there are few road environments suited for autonomous car.
from autonomousdrivingcookbook.
Neighborhood and Landscape are downloaded from the Unreal store. Hawaii and City are built by the AirSim team; the assets for those are not currently available for download.
from autonomousdrivingcookbook.
Hello, I have not found your answer about the range of steering angles. Can you tell me again? And how is the label of the steering angle normalized to [-1, 1]? Is there a formula or reference?
from autonomousdrivingcookbook.
Please help!!!
I have questions relating to gear in AirSim document.
What attribute in AirSim_rec indicates when the vehicle is backing up or in reverse?
What gear value indicates reverse
Can we predict forward/reverse movement along side steering angle to allow the vehicle correct itself in case it hits an obstacle.
Thank you in anticipation.
from autonomousdrivingcookbook.
Related Issues (20)
- Received an empty batch. Batches should at least contain one item.
- Gear attribute in airsim_rec.txt
- Train Model Keras Issue HOT 1
- no Cooking HOT 2
- ValueError: cannot reshape array of size 1 into shape (0,0,4) HOT 1
- Fails to create test.h5 and eval.h5 in DataExplorationAndPreparation HOT 2
- Modifications for throttle prediciton
- Getting IndexError: list index out of range while running TrainModel.ipynb ([in 5]). HOT 2
- When sending the steering angle to Carclient ,should the predition angle multiply 0.69 ? HOT 1
- JSONDecodeError HOT 1
- Mr. Spryn! How can I change the Generator.py and Cooking.py to store the images in the batches in the same order as they are in the folders and then entered into the model for train?
- Kaggle AirSim End-to-End Learning to share HOT 1
- File not found error
- Help! training not starting! #urgent HOT 6
- AirsimE2EDeepLearning code seems to change the tone of my image data HOT 2
- Dataset link does not work HOT 5
- This repo is missing important files HOT 1
- AD_Cookbook_AirSim.7z download link do not work! help! HOT 3
- Do not suit for uav
- Lane Following and Collision Avoidance for Self-Driving Cars
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from autonomousdrivingcookbook.