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Fall 2012
Crane lift path planning is time-consuming, prone to errors, and requires the practitioners to have exceptional visualization abilities, in particular, as the construction site is congested and dynamically changing. This research presents a methodology based on robotics motion planning to...
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Fall 2023
Unique challenges arise when attempting to navigate unknown GPS-denied subterranean environments. To successfully explore these environments a vehicle much be able to reconcile the nonlinear dynamics of motion, accommodate for diverse terrain, adjust to static and moving obstacles, combat...
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Reinforcement Learning-enhanced Path Planning for Mobile Cranes in Dynamic Construction Environments: A Virtual Reality–Simulation Approach
DownloadFall 2024
This work presents a novel approach to constructing site crane path planning using reinforcement learning and virtual-reality simulations. The approach involves a comprehensive simulation model that includes an agent, actions, states, environment, and a reward system. After extensive training...