ROSIntegration
carla
ROSIntegration | carla | |
---|---|---|
4 | 22 | |
391 | 10,516 | |
0.8% | 1.6% | |
6.5 | 9.4 | |
7 days ago | 2 days ago | |
C++ | C++ | |
MIT License | MIT License |
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ROSIntegration
- Unity VS Unreal which one you recommand for ROS (am a biginner for all three)
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ROSIntegration plugin
I've recently been working with ROSIntegration, does anyone have any examples of it's use? My publishers haven't been working as well as expected.
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Unreal to Ros
I've been trying to publish controller locations from an Oculus device to a Baxter running ROS Kinetic. While I found a decent plugin that seems to work on a basic level, the subscriber isn't reading it correctly. Is anyone familiar with ROSIntegration? Even just some examples of functional code using that plugin would be very helpful.
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Best Sim2Real Engine?
I would say this still depends on your use-case. Unity provides potentially high visual fidelity for image based learning etc. (like Unreal, for which there is this: https://github.com/code-iai/ROSIntegration ). The physics engine may be a bit simpler than in dedicated simulators to keep real-time > 60Hz up. (Unreal also uses PhysX)
carla
- Tesla braces for its first trial involving Autopilot fatality
- Mediocre Arduino Coder here: is there anyone that can offer their expertise on a virtual autonomous car project?
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Best Self Driving Cars Projects.
It sounds like you're looking for something like the CARLA simulator.
- What good Autonomous Driving simulators for research?
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Importing map from google maps
If you are looking for a different simulator, I would suggest using (Carla)[https://carla.org/] with ROS bridge and it also has an inbuilt support for OSM which worked flawlessly (you have to install it from source to get the OSM plugin).
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[D] Doing my (bachelor) thesis on RL. Which topic do you like best?
(3) I would suggest you use CARLA or TORCS for self-driving cars in RL as they are common test beds.
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Can someone build carla RL env for centOS for me?
carla env
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Car simulation RL environment - Carla centOS build
Link to carla
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Best way to simulate and train VSLAM based robot in virtual environments?
There are a few ways you could go with this. A fun recent trend has been to make simulators in the unreal engine for photorealistic training. If you wanted to spend your whole project on the simulator part you could make your own environment, but I highly recommend using an open-source sim package. If you don't care too much about photorealism, you could use gazebo just fine. I've also made small visual worlds in blender, then simulated with RVIZ. Here's a good one with a focus on aerial robotics: https://theairlab.org/tartanair-dataset/ You could also give CARLA a spin for autonomous vehicles: https://carla.org/
- Open-source simulator for autonomous driving research
What are some alternatives?
EpicSurvivalGame - Third-person Survival Game for Unreal Engine (Sample Project)
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
PBCharacterMovement - HL2-style, classic FPS movement for Unreal Engine implemented in C++
simulator - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles
UnrealROS - An Unreal Engine plugin that provides a ROS message publish/subscribe interface over TCP using the rosbridge protocol.
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
RuntimeMeshComponent - Unreal Engine 4 plugin component for rendering runtime generated content. [Moved to: https://github.com/TriAxis-Games/RealtimeMeshComponent]
apollo - An open autonomous driving platform
ros-sharp - ROS# is a set of open source software libraries and tools in C# for communicating with ROS from .NET applications, in particular Unity3D
webots - Webots Robot Simulator
Unity-Robotics-Hub - Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.
gym - A toolkit for developing and comparing reinforcement learning algorithms.