25 May 2012 Robust mobility in human-populated environments
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Abstract
Creating robots that can help humans in a variety of tasks requires robust mobility and the ability to safely navigate among moving obstacles. This paper presents an overview of recent research in the Robotics Collaborative Technology Alliance (RCTA) that addresses many of the core requirements for robust mobility in human-populated environments. Safe Interval Path Planning (SIPP) allows for very fast planning in dynamic environments when planning timeminimal trajectories. Generalized Safe Interval Path Planning extends this concept to trajectories that minimize arbitrary cost functions. Finally, generalized PPCP algorithm is used to generate plans that reason about the uncertainty in the predicted trajectories of moving obstacles and try to actively disambiguate the intentions of humans whenever necessary. We show how these approaches consider moving obstacles and temporal constraints and produce high-fidelity paths. Experiments in simulated environments show the performance of the algorithms under different controlled conditions, and experiments on physical mobile robots interacting with humans show how the algorithms perform under the uncertainties of the real world.
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Juan Pablo Gonzalez, Juan Pablo Gonzalez, Mike Phillips, Mike Phillips, Brad Neuman, Brad Neuman, Max Likhachev, Max Likhachev, } "Robust mobility in human-populated environments", Proc. SPIE 8387, Unmanned Systems Technology XIV, 83870Z (25 May 2012); doi: 10.1117/12.918948; https://doi.org/10.1117/12.918948
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