Just an idea: if you could try to establish a known colour or texture of the floor using computer vision then avoid anything that doesn't look like the floor. That's what I do when I walk cautiously.
Probably the most robust floor detector for a "very unstructured environment" would be a CNN trained to segment floor vs not-floor. If you have the budget, one way to get a training dataset is to create one using amazon turk to manually label a lot of images.
Here's a couple slides showing existing deep learning segmentation approaches and software that I think look promising.
https://www.slideshare.net/danielsnider/deep-learning-segmentation
Here's a list of deep learning segmentation publications:
https://handong1587.github.io/deep_learning/2015/10/09/segmentation.html
Another list of deep learning computer vision:
https://github.com/kjw0612/awesome-deep-vision
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