Enabling the full promise of robotics in agriculture requires reliable detection and tracking of human coworkers so that people and machines can effectively and safely perform required tasks. Many agricultural machines are powerful and potentially dangerous, and certain tasks require humans to work closely to these machines. Other applications may need to enforce a safety buffer, and agricultural fields generally have minimal access controls. Even for smaller agricultural robots, it is often important for them to understand where the people in their environment are to effectively complete their tasks.

Our previous work resulted in a spatially distributed multi-vehicle system of autonomous tractors that shared task responsibilities with multiple human co-workers to accomplish agricultural operations in a citrus orchard. This system has demonstrated over 2400km of autonomous operation and performed significant useful work at a higher productivity level than current methods. The system includes a sophisticated obstacle detection system, but a key limiting factor was the reliable detection of people when partially occluded by tree branches and weeds or when lying on the ground or in other non-standard poses. [1] [2]

[1] Carnegie Mellon University. “Integrated Automation for Sustainable Specialty Crops.” 

[2] S. J. Moorehead, C. K. Wellington, B. J. Gilmore, and C. Vallespi, “Automating orchards: A system of autonomous tractors for orchard maintenance,” in IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) Workshop on Agricultural Robotics, 2012.