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.

Amid rising tensions in the South China Sea, the People's Liberation Army (PLA) has developed a low-cost fast deployable air defense system using radar reflector balloons to protect military facilities from aerial attacks. In the era of AI technology, the Chinese military is opting for a rather simplistic method to protect critical infrastructure. The PLA demonstrated its latest technique at a joint drill, called the Zhejiang Golden Shield-22, conducted by the Chinese military and local units in November. It involved the use of radar reflector balloons to safeguard military facilities in case of a long-range missile or drone attack, according to a report on The War Zone. It included the deployment of AD air balloons on UAVs avenues of approach&energy assets visual camouflage (Ukraine lesson learnt) pic.twitter.com/m21KrBIVnZ