Dear Abhijit Khadatkar

I am not skilled in practical control or vision-based motion for autonomous vehicles or robots. But to m my humble knowledge, I think the best vision-based motion planning for advanced and sustainable control, is by utilizing a camera which has the capability to scan the environment in 3D. However, I think for the case of your problem, some other simpler technologies are also available, but as I already hinted, I have no idea about the specific cameras or firms developing such cameras, because I have never worked with a real control system, although my theoretical background is fair.

Dear Saeb AmirAhmadi Chomachar,

Thank you for your reply.

Can you provide the details or reference of some simpler technologies that you have pointed out, if possible.@

Dear Abhijit Khadatkar

You are welcome. As I had already underlined, I have no knowledge about such cameras. I have never seen such cameras in my hand or any other place. I have not also seen any technical online video in detail about them . I know no detail about the cameras. I only suggested my idea through the theoretical scope. I discriminated between 3D cameras and 2D cameras. I had seen a video from Boston Dynamics Atlas robot and also in TV, in which some cameras render the environment image in 3D scan and can analyze the environment for collision avoidance. A 3D scanner camera is suitable for advanced motion planning. But I guess some simpler cameras you could possibly use for your case. I mean a camera which can distinguish between the rough terrain where the farms are bordered, and the traction where the crops are grown. This could be simply available by a camera which could detect two different colors: color of row crop, and the curb obstacles along borders of any farm. There might be no need for an advanced 3D scanner camera, so long as a simple camera can distinguish dark and light fields and tractions over the farming land, based on their color (grey and black). This is all I knew.