This program will develop technologies and capabilities that will lead to fully autonomous cooperative multi-robot systems for exploration of large rough terrain. The multi-robot team extends data gathering and mapping capability for future missions through heterogeneous capabilities and adaptive task planning. Configurations will enable optimized multi-robot application in unknown rough terrain. The specific development is a platform developed around a concept mission to explore a lunar lava tube through entering a skylight. The platform developed will be broadly applicable to similar explorations of rough and/or subsurface planetary environments, including caves, craters, cliffs, or rock fields. Additionally, low-cost robotic team members are configured to exploit operation only in the shelter of subsurface environments without the stringent requirements for survival of radiation and thermal variations at the surface; this is applicable as a strategy to reduce the cost of multi-robot mission implementations.
Multi-robot operations for mapping in a subsurface void are broadly applicable to numerous terrestrial applications. Potential applications are summarized below: Following or during a natural disaster such as an earthquake or flood, multiple robot teams can be deployed to assess and respond to the situation. Sub-teams of agents perform various categories of tasks such as monitoring, inspection, search and rescue, excavation, evacuation, and distribution of aid. In mining, activities such as cutting coal, creating roof supports, and transporting coal may take place simultaneously in various locations in a mine and be performed by a combination of humans and machines (including robots). The machines responsible for each of these activities must be efficiently coordinated. In construction, activities such as excavation, earth-moving, transportation of building materials, and assembly take place simultaneously at different locations on the construction site. Again, the machines responsible for each of the activities must be efficiently coordinated.