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Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Human-robot shared autonomy techniques for vehicle navigation hold promise for reducing a human driver's workload, ensuring safety, and improving navigation efficiency. However, because typical techniques achieve these improvements by effectively removing human control at critical moments, these approaches often exhibit poor responsiveness to human commands—especially in cluttered environments. In this paper, we propose a novel goal-blending shared autonomy (GBSA) system, which aims to improvedoi:10.1609/aaai.v35i7.16742 fatcat:4vmjyjhpa5dptjtrlaue5olgoq