Development of an Agricultural Robot Taskmap Operation Framework

摘要

ABSTRACT Robotic technology in precision crop farming has the potential to minimize inputs, such as labor, fertilizer, or plant protection products, maximizing the net yield while reducing the environmental impact. To maximally exploit the benefits of precision crop farming, it has to be applied continuously over multiple years, which requires (robotic) technology for a wide range of agricultural operations. Researchers need access to (noncommercial) robot platforms with complete mechanical and software controllability to investigate new applications that could unlock the true potential of precision farming. This study presents the agricultural robot taskmap operation framework (ARTOF), which provides common functionality for robots with different vehicle configurations to execute task maps in crop farming applications based on global navigation satellite system positioning. The two‐layered software stack has a mechatronic layer and an operational layer. The mechatronic layer performs motion control and includes machine safety to meet the required performance level in correspondence with European regulations. The operational layer performs autonomous implement and navigation control. Add‐ons interact with the operational layer using the ARTOF Redis interface and increase flexibility. Hardware‐in‐the‐loop testing enables static end‐to‐end testing and minimizes the developing time and operational faults when developing new functionality. To demonstrate the framework's flexibility, it was integrated into four in‐house developed and modified agricultural robots with four‐wheel drive, four‐wheel steering (4WD4WS), skid steering, and Ackerman steering vehicle configurations. These robots performed 11 applications under real practice conditions in arable farming and horticulture for—in total—more than 11 km of field application. The power consumption, navigation accuracy, and software usability were evaluated. An average navigation accuracy of 1.0 cm was achieved during hoeing with a 4WD4WS robot using the newly developed navigation controller. This new open‐source software framework enables the rapid validation of agricultural robotic research to broaden the number of precision crop farming applications and fully exploit their potential.