Articulated robots are being entrusted with an ever-increasing range of manufacturing operations across various sectors. This is stemmed, among other factors, by the broad movement range, flexibility, and small footprint of these robots. However, when it comes to high-payload operations, gantry robots, with their rigid construct, are still the option of choice. This is particularly true when precision is of concern. Unfortunately, a rigid gantry setup is difficult to implement in space especially considering weight constraints and the need for flexibility. Modular robotic kinematic systems offer process flexibility and diversity. Robotic kinematic systems are already being used for in-space applications. This proposal is aimed at developing a machine learning-based software solution that would allow for high-precision, high-payload manufacturing operations to be carried out autonomously using multiple articulated robots. The work targets robotic sheet metal forming, which given its versatility and simplicity is an ideal operation for both on-ground and in-space manufacturing/repair of metal parts. The robotic forming cell consists of two heterogenous, 6-axis robots mounted on two linear tracks and a real-time monitoring and control system. The robots must work in coordination with each other to incrementally form a sheet of metal into a part based on an input CAD file. This work introduces a software solution which addresses a number of challenges. First, both robots need to be synced while experiencing differing loading conditions imposed by the forming operation (e.g., due to variation in friction). Second, the positioning of the two robots need to be dynamically adjusted to make sure the overall compliance of the robotic system is minimized. Third, the system monitors the forming operation in real-time and assesses its deviation against the initially defined path. The feedback from the monitoring system needs to be actively used to update the predefined path.
First, the developed software modules and control strategies can be adopted to enable autonomous in-space manufacturing and on-orbit assembly operations. Second, the robotic cell can be used to manufacture lightweight parts for various NASA programs (e.g., components for solar arrays, lander systems, and ultra-lightweight dewars). Third, the forming technology can be adopted for in-space manufacturing and in-situ resource utilization (e.g., repurposing metals from spacecraft to manufacture structures or molds to build habitats).
The robotic forming cell will be used to manufacture and supply sheet metal parts to a multitude of industries (e.g., aerospace, automotive, energy, architecture). The system allows for rapid iteration over design/material at reduced time and cost. It also enables fabrication of parts with previously impossible-to-achieve performance. Composite mold fabrication is an application of the technology.