DON is the Distributed Observer Network. It is a game-based tool combining the analysis capabilities of NASA’s distributed simulation capabilities with interface standards (the MPC telemetry definition) and video game technologies to record and share 4D data associated with analysis activities.
The RE-RASSOR Shoulder team focused on the creation of a viable replacement for the current, $1,000+, NASA mini-RASSOR component. Replacement of this joint enables the full RE-RASSOR excavator to be built without the need the high cost, steel components. The solution is a compound reduction gear driven by a NIMA 23 motor.
The RE-RASSOR Arm project integrated past arm software with the FSI provided Arm to provide arm movement and management software. The team combined created both the manual movement abilities as well as basic automatic functions for parking and homing the arm.
The RE-RASSOR Cart project combined the ROS 1 and ROS 2 software with the current hardware design to create a turn-key rover for use in the classroom or to support research in the field. The host processor is a Raspberry Pi 4 that configures the Arduino controller, manages the remote-control interface (mobile device via wi-fi) and passes commands to the Arduino to drive the RE-RASSOR robot. The final deliverable is an image file for Pi and instructions for use. The final product was successfully demonstrated on the electrical mockup (Pi, Arduino, 4 motors).
The Sim SmackDown, or Simulation Exploration Experience, is a long running, international cooperative event combining Industry, Academia and Government to simulate future Lunar and Martian settlement concepts. NASA provides mentors, tools, architectures and challenges; Industry provides tools and standards; and Academia provides technologies and students from around the world. The UCF team is responsible for both the Lunar Base and the complete computing infrastructure for the entire simulation.
NASA created an indoor robotics arena for the their Lunabotics Competition. The desire was to run small rovers in smaller competitions for middle and high school students. The team ported the EZ-RASSOR software to the NASA hardware platform and developed competition management tools for use by the Education team. The Software was complete on time, the NASA hardware is still in development.
The Marsupial Rover is student developed and based on a NASA SwampWorks challenge. The goal is to leverage EZ-RASSOR software, NASA concepts, RE-RASSOR and Phoenix (small and large rovers) to create an autonomous resource harvesting system for the Moon or Mars.
EZ-RASSOR is student developed, NASA Sponsored, open sources software for rover management and operation; details are available on the GitHub. The goal is to create a generalized rover management system suitable for remote control use, but extendable to autonomous navigation, swarm operation and local decision making. EZ-RASSOR began as a ROS 1.0 project. The 2021/22 team converted the code base to work in the ROS 2.0 environment while addressing ROS shortfalls in areas that impacted overall performance and RE-RASSOR goals.
The ISRU (In Situ Resource Utilization) Performance team created a discrete event simulation for lunar resources and the intended harvester and refinery systems. The simulation includes rover transit times, raw material locations, material characteristic (depth, % water, travel time) prospecting systems and beneficiation systems. This allows investigation of ISRU system performance and associated sensitivities to resource locations, resource quality, deployed systems and overall process time.
The overall goal of our project is to level an area on the moon using a SWARM of EZ-RASSOR rovers so that a landing pad may be built. In doing this, we will illustrate that these low-cost rovers are to do high level tasks autonomously. Our project has several different aspects. We developed an algorithm that uses a digital elevation model of an area to create an unordered set of instructions which may be completed by a SWARM of rovers to level the area described by the digital elevation model in an efficient manner.