System and method for full-stack verification of autonomous agents
作者： Ros Sanchez German
DOI:
关键词: Autonomous agent 、 Stack (abstract data type) 、 Sensory input 、 Noise (video) 、 Object detection 、 Information data 、 Ground truth 、 Computer science 、 Artificial neural network 、 Real-time computing
摘要: A method for full-stack verification of autonomous agents includes training a neural network to learn noise model associated with an object detection module agent system vehicle. The also replacing the and sensory input ground truth information apply surrogate function information. further verifying including trained in response simulate sensor data at least planner system. controlling behavior vehicle using verified module.
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