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This paper proposes a method of searching for missing people in mountains by UAVs (Unmanned Aerial Vehicles) based on beacon signals. This method alternately updates the distribution of estimated target position and unknown parameters by particle filtering, and determines the next best observation location based on the idea of the uncertainty sampling. We will show how this method can be integrated...
Within the complex driving environment, progress in autonomous vehicles is supported by advances in sensing and data fusion. Safe and robust autonomous driving can only be guaranteed provided that vehicles and infrastructure are fully aware of the driving scenario. This paper proposes a methodology for feature uncertainty prediction for sensor fusion by generating neural network surrogate models directly...
This paper investigates the robust weighted fusion estimation problem of multi-sensor systems with mixed uncertainties, including stochastic parameter uncertainties, missing measurements and uncertain noise variances. The stochastic parameter uncertainties are described by multiplicative noise. Especially, the variances of both the multiplicative and additive noises are uncertain. By introducing two...
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