Résumé
The operation of autonomous robots in the agricultural domain requires compliance with the regulatory aspects of the process. For instance, the improper spraying of chemicals near water bodies (e.g., pesticides or fertilizers) may cause significant environmental damage and, therefore, is strictly regulated at the legislation level. In this paper, we introduce a reasoning-enhanced framework to operate autonomous robots spreading chemicals near water bodies. Our framework leverages and extends semantic web vocabularies to integrate regulatory constraints and environmental conditions where the robot is operating. Then, it uses rules and reasoning to detect violations on real-time data generated by the autonomous robot. The inference of violations subsequently triggers actions controlling the robot behavior, but can also be transparently explained in our framework, thereby avoiding the robot to behave as a black-box to the supervising technician. Our approach has been implemented, and its feasibility showcased in a simulation environment.