Experimental study demonstrates unified environmental constraint mapping for autonomous agricultural robots, highlighting flexible deployment across diverse field environments.
Robust navigation is a key ability for agricultural robots. Such robots must operate safely minimizing their impact on the soil and avoiding crop damage. This paper proposes a method for unified incorporation of the application-specific constraints into the navigation system of robots deployed in different agricultural environments. The constraints are incorporated as an additional cost-map layer into the ROS navigation stack. These so-called Agri-Cost-Maps facilitate the transition from the tailored navigation systems typical for the current generation of agricultural robots to a more flexible ROS-based navigation framework that can be easily deployed for different agricultural applications. We demonstrate the applicability of this framework in three different agricultural scenarios, evaluate its benefits in simulation and demonstrate its validity in a real-world setting.
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Ponnambalam et al. (2020) studied this question.