Influence of incorrectly calibrated vehicle environment sensors on vehicle self-diagnosis and ADAS systems in carla simulation
how Development of a virtual map using vehicle environment sensors in carla simulation ??
if someone have idea or have project / literature review , please share with me.
thanks in advance,
smit patel
i want to generate scene in Carla simulator while ego car is change in lane condition. To simulate the problem and what will be outcome of the mention problems.
Related
i am doing final year project as lane tracking using a camera. the most challenging task now is how i can measure distance between the camera (the car that carries it actually) and the lane.
While the lane is easily recognized (Hough line transform) but i found no way to measure distance to it.
given the fact that there is a way to measure distance to object in front of camera based on Pixel width of the object, but it does not work here be because the nearest point of the line, is blind in the camera.
What you want is to directly infer the depth map with a monocular camera.
You can refer my answer here
https://stackoverflow.com/a/64687551/11530294
Usually, we need a photometric measurement from a different position in the world to form a geometric understanding of the world(a.k.a depth map). For a single image, it is not possible to measure the geometric, but it is possible to infer depth from prior understanding.
One way for a single image to work is to use a deep learning-based method to direct infer depth. Usually, the deep learning-based approaches are all based on python, so if you only familiar with python, then this is the approach that you should go for. If the image is small enough, i think it is possible for realtime performance. There are many of this kind of work using CAFFE, TF, TORCH etc. you can search on git hub for more option. The one I posted here is what i used recently
reference:
Godard, Clément, et al. "Digging into self-supervised monocular depth estimation." Proceedings of the IEEE international conference on computer vision. 2019.
Source code: https://github.com/nianticlabs/monodepth2
The other way is to use a large FOV video for a single camera-based SLAM. This one has various constraints such as need good features, large FOV, slow motion, etc. You can find many of this work such as DTAM, LSDSLAM, DSO, etc. There are a couple of other packages from HKUST or ETH that does the mapping given the position(e.g if you have GPS/compass), some of the famous names are REMODE+SVO open_quadtree_mapping etc.
One typical example for a single camera-based SLAM would be LSDSLAM. It is a realtime SLAM.
This one is implemented based on ROS-C++, I remember they do publish the depth image. And you can write a python node to subscribe to the depth directly or the global optimized point cloud and project it into a depth map of any view angle.
reference: Engel, Jakob, Thomas Schöps, and Daniel Cremers. "LSD-SLAM: Large-scale direct monocular SLAM." European conference on computer vision. Springer, Cham, 2014.
source code: https://github.com/tum-vision/lsd_slam
I use ARWorldMap to save the state of the scene and restore it later. I use the code recommended by Apple in the examples. There is a problem: lighting conditions, if I record a map of the world in a room with bright lighting, it is impossible to restore the position of the content in medium light, and in reverse order it is analgesic.
Do you have any ideas how to fix this so that the lighting conditions do not affect the recovery of the session with the world map?
Save & load lighting parameters retrieving ARKit's Light Estimation values. However, if you want AR app can recognize different lighting conditions of some environment you should generate .mlmodel based on several hundreds of images (using Create ML app) and feed it to Vision SDK for classification. Although, to be honest, I highly doubt that a Vision approach will be working sanely. So for accuracy, you may use light estimation parameters' values in conjunction with Vision's classification results. You need to try.
If you have a device with LiDAR it should be possible to regenerate the World Map in other lightning conditions. I have the same issue like you and I am working on it. I still don't have a clear solution at the moment. I've also contacted Apple on this, without any succes (no documents or demo's). If I know how to solve this I let you know.
I am looking for a indoor positioning/2d motion tracking system for small robot cars (1:8 scale RC cars). We want to use the system as a ground truth for the development of autonomous driving applications, so looking for an accuracy of a few millimeters. The testing area is around 10x10m.
The cars are running ROS (Robotic Operating System), so an existing implementation would be nice.
A known solution is a OptiTrack motion capture system, but with a cost of >10kEuro this is way above our budget of around 1.5kEuro. I have also been looking in using HTC Vive trackers with OpenVR, but I am not sure if this is a reliable solution.
Any idea would be very welcome!
I'm having some difficulties understanding the concept of teleoperation in ROS so hoping someone can clear some things up.
I am trying to control a Baxter robot (in simulation) using a HTC Vive device. I have a node (publisher) which successfully extracts PoseStamped data (containing pose data in reference to the lighthouse base stations) from the controllers and publishes this on separate topics for right and left controllers.
So now I wish to create the subscribers which receive the pose data from controllers and converts it to a pose for the robot. What I'm confused about is the mapping... after reading documentation regarding Baxter and robotics transformation, I don't really understand how to map human poses to Baxter.
I know I need to use IK services which essentially calculate the co-ordinates required to achieve a pose (given the desired location of the end effector). But it isn't as simple as just plugging in the PoseStamped data from the node publishing controller data to the ik_service right?
Like a human and robot anatomy is quite different so I'm not sure if I'm missing a vital step in this.
Seeing other people's example codes of trying to do the same thing, I see that some people have created a 'base'/'human' pose which hard codes co-ordinates for the limbs to mimic a human. Is this essentially what I need?
Sorry if my question is quite broad but I've been having trouble finding an explanation that I understand... Any insight is very much appreciated!
You might find my former student's work on motion mapping using a kinect sensor with a pr2 informative. It shows two methods:
Direct joint angle mapping (eg if the human has the arm in a right angle then the robot should also have the arm in a right angle).
An IK method that controls the robot's end effector based on the human's hand position.
I know I need to use IK services which essentially calculate the
co-ordinates required to achieve a pose (given the desired location of
the end effector). But it isn't as simple as just plugging in the
PoseStamped data from the node publishing controller data to the
ik_service right?
Yes, indeed, this is a fairly involved process! In both cases, we took advantage of the kinects api to access the human's joint angle values and the position of the hand. You can read about how Microsoft research implemented the human skeleton tracking algorithm here:
https://www.microsoft.com/en-us/research/publication/real-time-human-pose-recognition-in-parts-from-a-single-depth-image/?from=http%3A%2F%2Fresearch.microsoft.com%2Fapps%2Fpubs%2F%3Fid%3D145347
I am not familiar with the Vive device. You should see if it offers a similar api for accessing skeleton tracking information since reverse engineering Microsoft's algorithm will be challenging.
I am soon to start with Microsoft Robotics Studio.
My question is to all the gurus of MSRS, Can simple simulation (as obstacle avoidance and wall following) be done without any hardware ?
Does MSRS have 3-dimensional as well as 2-dimensional rendering? As of now I do not have any hardware and I am only interested in simulation, when I have the robot hardware I may try to interface it!
Sorry for a silly question, I am a MSRS noob, but have previous robotics h/w and s/w experience.
Other than MSRS and Player Project (Player/Stage/Gazebo) is there any other Software to simulate robots, effectively ?
MSRS tackles several key areas. One of them is simulation. The 3D engine is based on the AGeia Physics engine and can simulate not only your robot and its sensors, but a somewhat complex environment.
The demo I saw had a Pioneer with a SICK lidar running around a cluttered appartment living room, with tables, chairs and etc.
The idea is that your code doesn't even need to know if it's running on the simulator or the real robot.
Edit:
A few links as requested:
Start here: http://msdn.microsoft.com/en-us/library/dd939184.aspx
alt text http://i.msdn.microsoft.com/Dd939184.image001(en-us,MSDN.10).jpg
Then go here: http://msdn.microsoft.com/en-us/library/dd939190.aspx
alt text http://i.msdn.microsoft.com/Dd939190.image008(en-us,MSDN.10).jpg
Then take a look at some more samples: http://msdn.microsoft.com/en-us/library/cc998497.aspx
alt text http://i.msdn.microsoft.com/Cc998496.Sumo1(en-us,MSDN.10).jpg
simple answer is yes, MRDS simulator and player/stage have very similar capabilities. MRDS uses a video game quality physics engine under the hood, so you can do collisions, and some basic physics on your robots, but its not going to be the level of accuracy of a matlab simulation (on the flip side its realtime and easier to develop with though). You can do a lot in MRDS without any hardware.
MRDS uses some pretty advanced programming abstractions, so can be a bit intimidating at first, but do the tutorials, and the course that has been posted to codeplex "software engineering for robotics" and you will be fine. http://swrobotics.codeplex.com/