Automated Turf Management

To achieve complete automation on golf courses, we are developing capabilities for:

• Reliable obstacle detection.
  
• Must be able to find obstacles as small as a golf ball, while not generating false positives.
  
• Also must detect all true obstacles to keep the vehicle safe.
  
• Precise navigation. Must be able to operate with cm level precision to create the cross-hatch patterns seen on premier golf courses.
  
• Effective coverage. Must be able to create patterns that cover the entire fairway in an efficient manner.
  

Benefits

The key benefits of this technology are

• reduction in reliance on skilled operators, and
  
• expanded hours of golf course availability.
  

Approach

The first approach to obstacle detection is

• color segmentation, which is the ability to distinguish obstacles based on color. We are developing a method that is robust to changes in color due to shadows and atmospheric conditions.
  

• stereo based homography, to detect objects which lie above the ground plane.
  

• Sick^TM Laser scanner as a backup detection system, for instances where vision-based methods fail.
  

Status

• As of December 2000, we have implemented path tracking and obstacle detection on the mower. We are doing runs of over 1 km in length. The obstacle detection system has been enhanced with the addition of a Sick laser sensor, for use in validating obstacles in situations where vision cannot perform.
  
• In August 2000, we held a successful demonstration of this system in which we performed over 50 iterations of our demonstration. Each iteration consisted of mowing six rows, each 10 meters long.