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• W4285237227 abstract "This letter proposes a new structured method for a moving agent to predict the paths of dynamically moving obstacles and avoid them using a risk-aware model predictive control (MPC) scheme. Given noisy measurements of the a priori unknown obstacle trajectory, a bootstrapping technique predicts a set of obstacle trajectories. The bootstrapped predictions are incorporated in the MPC optimization using a risk-aware methodology so as to provide probabilistic guarantees on obstacle avoidance. We validate our methods using simulations of a multi-rotor drone that avoids various moving obstacles." @default.
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• W4285237227 date "2023-01-01" @default.
• W4285237227 modified "2023-10-10" @default.
• W4285237227 title "Moving Obstacle Avoidance: A Data-Driven Risk-Aware Approach" @default.
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• W4285237227 doi "https://doi.org/10.1109/lcsys.2022.3181191" @default.
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