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Achieving long term autonomy of robots operating in dynamic environments suchas farms remains a significant challenge. Arguably, the most demanding factorsto achieve this are the on-board resource constraints such as energy, planningin the presence of moving individuals such as livestock and people, andhandling unknown and undulating terrain. These considerations require a robotto be adaptive in its immediate actions in order to successfully achievelong-term, resource-efficient and robust autonomy. To achieve this, we proposea hierarchical framework that integrates a local dynamic path planner with alonger term objective based planner and advanced motion control methods, whilsttaking into consideration the dynamic responses of moving individuals withinthe environment. The framework is motivated by and synthesizes our recent workon energy aware mission planning, path planning in dynamic environments, andreceding horizon motion control. In this paper we detail the proposed frameworkand outline its integration on a robotic platform. We evaluate the strategy inextensive simulated trials, traversing between objective waypoints to completetasks such as soil sampling, weeding and recharging across a dynamicenvironment, demonstrating its capability to robustly adapt long term missionplans in the presence of moving individuals and obstacles for real worldapplications such as large scale farming.

A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming