While the focus of my efforts at the moment are on concepts for grazing, I thought I would also capture my thinking for locomotion...

The development steps I'm expecting are:

1. Move and steer on grassy terrain
2. Detect what is and isn't lawn and stay on the grass
3. Have a strategy for finding the sun to recharge when required
4. Move in a way that covers every part of the lawn as evenly as possible

So far I have had a few ideas:

• Number 1 should just be some knobbly 3D printed wheels on gear motors. Differential drive to steering and some kind of castor is probably easiest.
• For number 2 my lawn is surrounded by paving, sheds, raised beds and decking. I suspect that a combination of a downwards pointing colour sensor looking for green grass and some ultrasonic sensors may be enough.
• On number 3 my preferred concept is to use a magnetometer and drive north until the edge of the lawn, which should mean the sunniest area. I need some way to randomise the stopping point a little to avoid a dead patch of grass under the charging spot. Or the sheep could sleep on the paving just north of my lawn if that turns out to be easier,
• Number 4 is the most challenging. Many dumb algorithms would preferentially graze the edges or the middle, with corners likely to be least grazed. Hopefully a simple 'pong' bouncing algorithm should be good enough if the grazing is faster than the growing. If not I might have to put some intelligent navigation in the controller, but I don't want the complexity of SLAM and half baked algorithms are likely to be worse than random. Perhaps stripes using compass bearings and range finders might be a simpler alternative.

Once again, if you have any bright ideas, let me know in the comments...

Until next time,

Jellmeister