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• W2220231182 abstract "This paper presents a stochastic approach for automatic collision avoidance for tele-operated unmanned aerial vehicles (UAVs). Collision detection and mitigation in the presence of uncertainty is an important problem to address because on-board sensing and state estimation uncertainties are inherent in real-world systems. A feedforward-based algorithm is described that continually extrapolates the future trajectory of the vehicle given the current operator control input for collision avoidance. If the predicted probability of a collision is greater than a user-defined confidence bound, the algorithm overrides the operator control input with the nearest, safe command signal to steer the robot away from obstacles, while maintaining user intent. The algorithm is implemented on a simulated quadrotor helicopter (quadcopter) with varying amounts of artificial uncertainty. Simulation results show that for a given confidence bound, the aerial robot is able to avoid collisions, even in a situation where the operator is deliberately attempting to crash the vehicle." @default.
• W2220231182 created "2016-06-24" @default.
• W2220231182 creator A5010222209 @default.
• W2220231182 creator A5027538794 @default.
• W2220231182 creator A5078661988 @default.
• W2220231182 date "2015-09-01" @default.
• W2220231182 modified "2023-09-25" @default.
• W2220231182 title "Stochastic automatic collision avoidance for tele-operated unmanned aerial vehicles" @default.
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• W2220231182 doi "https://doi.org/10.1109/iros.2015.7354054" @default.
• W2220231182 hasPublicationYear "2015" @default.
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