Robotics path optimization
Zach CardozaTulare, CA
A Python and Jupyter study I built at Kaweah Tech for an early-stage automated farm-management startup. The client had a target robot in design, but most of its operating parameters had not been measured because the prototype was not finished. From the ideal-robot dimensions, we worked out the operating envelope (speeds for unloaded and loaded operation, turning radii, and the trailer tracking paths through a turn) and then used the derived envelope to plan optimal coverage on the field they were considering. The notebook walked through robot count and field suitability for the operation as the client had described it.
- Role
- Founder
- Client
- Automated farm-management startup (anonymized)
- Dates
- 2024
- Tech
- Python
- Jupyter
- Optimization libraries
Most path-planning work starts with a known robot and a known field. This one started with neither. The client had a target robot in design, but most of its operating parameters had not been measured because the prototype was not finished. The field they were considering was real land, but row spacing, headland geometry, and gate access were all still in flux. We were doing path planning before any of the inputs to path planning existed.
The client gave me the dimensions of the ideal robot they were designing (chassis, wheelbase, hitch position, and the trailer it was meant to pull). From there I worked out the operating envelope: speeds for unloaded and loaded operation, the turning radius at each load condition, and the trajectory the trailer would track behind the tractor through a turn.
Once the envelope was in place, the Jupyter notebook compared a few path-planning approaches against a parameterized field model so the client could see the trade-offs side by side. Coverage rate against turn count. Path length against headland margin. The output was a recommended fleet size, a recommended path pattern, and a sensitivity analysis showing which inputs mattered most: which robot dimensions, which field configurations.
The engagement was a one-off. The notebook and the writeup went to the client. What they do with it from here is up to them.