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Safe Chance-constrained Model Predictive Control under Gaussian Mixture Model Uncertainty
We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty.
Safe Motion Planning against Multimodal Distributions based on a Scenario Approach
We develop a computationally efficient, scenario-based approach that solves the motion planning problem with high confidence given a quantifiable number of samples from the multimodal distribution.
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