Efficient Probabilistic Collision Detection for Non-Gaussian Noise Distributions
IEEE Robotics and Automation Letters(2020)
摘要
We present an efficient algorithm to compute tight upper bounds of collision probability between two objects with positional uncertainties, whose error distributions are represented with non-Gaussian forms. Our approach can handle noisy datasets from depth sensors, whose distributions may correspond to Truncated Gaussian, Weighted Samples, or Truncated Gaussian Mixture Model. We derive tight proba...
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关键词
Collision avoidance,Probabilistic logic,Uncertainty,Computational modeling,Robots,Sensors,Shape
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