To help NASA achieve there current and future space exploration goals, Geisel Software and University of Nevada, Las Vegas are proposing a solution that will allow for collaborative mobility and manipulation in a heterogeneous robotic environment. This includes the ability for robots to handle problem solving on their own, as well as both high-level and direct control from humans, when desired. Our open system not only solves these problems, but it allows NASA to use their existing robots, future robots and those of other vendors in a fully collaborative environment. This system increases the efficiency of space exploration while decreasing the risk to human explorers. It also adds the resiliency and redundancy necessary for the harsh environments in space and other planetary bodies.
Realistic, high-quality graphics simulation of the autonomous ground and aerial vehicles in space exploration is an essential tool due to difficulties in experimentation under extreme space environments. A well-designed robot simulator makes it possible to rapidly test algorithms and design autonomous vehicles based on more realistic scenarios. This is the first step in achieving a system that is collaborative, autonomous and seamlessly controllable by humans as necessary.
This proposal is for a realistic simulator and algorithms for simulating with the capability of embedding physical data and a mechanism for solving the compute complexity issues inherent in swarming applications.
NASA has a requirement (via 2020 Technology Taxonomy document) to provide Collaborative Mobility and Collaborative Manipulation. The system created by UNLV and Geisel Software will allow NASA to solve problems such as mapping, localization, atmospheric transmission spectroscopy, electromagnetic radiation detection of all kinds, seismic and other planetary sensing, and many others.
This technology is important to lunar exploration as well as planetoids with atmospheres such as Mars, Venus, Jupiter, Titan and many others.
First responders face significant challenges during a nuclear accident. It is critical to locate radiological or nuclear materials or sources in a wide and clustered area, and it is one of the major challenges is acting decisively based on available real-time radiation data. This is one of numerous commercial applications already needing this solution.