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Smart method and system to create a virtual intelligent transit agent based on traffic workload Disclosure Number: IPCOM000252781D
Publication Date: 2018-Feb-08
Document File: 2 page(s) / 14K

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The Prior Art Database

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Use self-assembly robot for tunnel construction (three-layer approach) The main issue with current tunneling technology is the cost. Current estimates are around $1 billion per mile of tunnel. These costs come from the complexity of moving that much dirt out of the tunnel, having to constantly shore up the sides of the tunnels every 10-15 feet, which requires digging crews to stop the drill to shore up the walls, and the very slow speed at which these digging machines move. The novel contribution to knowledge is a more efficient way to move dirt and shore up tunnel walls while the drill continues to spin. The core novelty is the coordination and use of self-assembling robots to create tunnels and conveyor systems for use in tunneling systems. This approach can greatly increase the speed at which the drill moves, thus lowering overall costs. The approach uses three layers of self-assembly robots to shore up the tunnel and work as a conveyor belt. These "layers" are concentric rings that form around the tunnel walls. The first layer, the one closest to the dirt, becomes the tunnel wall itself. It shores up the dirt and acts as a guide rail for the layer on top. The second and third layers act in unison as a conveyor belt to pull the dirt back out from the drilling machine. Layer 3 is constantly moving "out" of the tunnel pulling the dirt with it, while Layer 2 is constantly feeding either new robots or robots recycled from Layer 1 that have finished dumping into the system, which either become Layers 1 or 3 depending on what is needed. The initial state is with the boring machine outside the dirt wall, with the self-assembling robots behind it. These form the first three rings to start the process. The drill then begins digging. The self-assembling robots continue following the boring machine into the tu...