Obstacle avoidance with pure Vision approach?
Hi
I would like to do obstacle avoidance using pure Vision approach. I will use ROS and Ubuntu as a framework. The application is in construction industry so would like to detect the material winch is handling by the crane to perform obstacle avoidance . My question is , if its possible to use only vision approach for obstacle avoidance where the distance form the camera to the object can be 30-40m. I will use the zoom for better approach. If its possible to use only Vision camera any starting algorithm to look at it?
Thanks
Well stereo camera setup is pure vision based , yes you can construct a disparity map which could then be used for depth . Depth can be used for the purpose of mapping while performing path planing keeping obstacle avoidance in mind .
https://www.stereolabs.com/
Check out this stereo camera , cost wise its a little on the higher side , but a lot can be achieved using this device .
I know this ZED camera. But the distance is quite long, as for some high rise buildings can be over 50 m easily and the depth information from the camera in that case can not be used. So is the distance a problem for pure vision approach?
What do you mean by "pure vision based approach"? No 3D information?
I mean only using Machine Vision Camera, no other sensors.
You need good contrast in order for stereo cameras to give you good depth information.
but if the distance is far , let say more then 50m how can be provided the depth information?
And is there any code using ROS, Neural Networks or Deep Learning, Machine Vision based obstacle avoidance code? Just o start it as Im beginner in this