The IVR interface includes: 1) a thin ferromagnetic material layer that allows robots to magnetically grip the DogTag, 2) a long-range optical fiducial printed and attached to the DogTag’s surface that allows the robot to determine relative pose and position of the object & 3)methods for attaching the DogTag to the desired object including rigid surfaces and soft-goods objects. We envision using our patented electropermanent magnet (EPM) based gripper for interfacing with the IVR DogTags. To enable these types of robotic interactions, Altius proposes leveraging our existing commercially available (TRL8/9) “DogTag” grapple fixture and developing a lightweight, low-cost, passive robotic magnetic interface (IVR DogTags) that can be attached to various habitat structures and objects. These robotic interaction aids ideally can serve three purposes: 1) helping robots determine their relative pose and position with respect to the target, and their relative location/pose inside or outside the habitat, 2) identifying what the objects are, especially if the objects are mobile like soft-goods bags, and 3) simplifying physical interactions with the object, including anchoring to and manipulating the object.
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Therefore, it is meaningful to fully develop, demonstrate, and validate this software tool in Phase II.įor deep-space habitats, especially ones left in orbit around a destination planet or Moon, astronaut time at the habitat will be both infrequent and very valuable and it would be extremely desirable for robots to outfit the habitat prior and to allow robots to perform maintenance and logistics tasks. While theoretically it may be possible to design robots to interact with a habitat designed without robotic interactions in mind, the addition of cooperative robotic interaction features can dramatically simplify and improve the robustness of the robotic outfitting hardware. As a feasibility study, the Phase I outcome will demonstrate the feasibility of the proposed LES approach for accurate simulation of NASA 22-in fan noise source diagnostic test. Much more accurate spatial discretization schemes will also be used for improving the prediction of turbulent eddies and acoustic waves. The proposed approach combines the advantages of those existing high-fidelity methods in literature for simulation of NASA 22-in fan noise source diagnostic test (SDT), i.e., the LES with the WALE SGS model for turbulence simulation and modeling, and the Cartesian mesh approach for rotor-stator coupling, and the consideration of the whole rotor and stator annulus in simulation. This SBIR project proposes to develop a computational tool for fan broadband noise prediction based on a large-eddy-simulation (LES) approach. Technical Abstract (Limit 2000 characters,
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