  Degraded rangelands undergo continual shifts in the appearance and
distribution of plant life. The nature of these changes however is subtle:
between seasons seedlings sprout up and some flourish while others perish,
meanwhile, over multiple seasons they experience fluctuating precipitation
volumes and can be grazed by livestock. The nature of these conditioning
variables makes it difficult for ecologists to quantify the efficacy of
intervention techniques under study. To support these observation and
intervention tasks, we develop RestoreBot: a mobile robotic platform designed
for gathering data in degraded rangelands for the purpose of data collection
and intervention in order to support revegetation. Over the course of multiple
deployments, we outline the opportunities and challenges of autonomous data
collection for revegetation and the importance of further effort in this area.
Specifically, we identify that localization, mapping, data association, and
terrain assessment remain open problems for deployment, but that recent
advances in computer vision, sensing, and autonomy offer promising prospects
for autonomous revegetation.
