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Found 6 papers, 0 papers with code
Gaussian Processes with State-Dependent Noise for Stochastic Control
In the proposed formulation, the residual model uncertainty consists of a nonlinear function and state-dependent noise.
Friction-Adaptive Stochastic Nonlinear Model Predictive Control for Autonomous Vehicles
The estimators output the estimate of the tire-friction model as well as the uncertainty of the estimate, which expresses the confidence in the model for different driving regimes.
Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles
To take the high mobility of vehicles into account, we consider the delay as a learning parameter and restrict it to be less than a tolerable threshold.
Exploiting Temporal Relations on Radar Perception for Autonomous Driving
We consider the object recognition problem in autonomous driving using automotive radar sensors.
Ranked #1 on
Multiple Object Tracking
on RADIATE
Automated Controller Calibration by Kalman Filtering
The control parameter calibration is driven by a training objective, which encompasses specifications on the performance of the dynamical system.
Sampling-based Algorithms for Optimal Motion Planning Using Closed-loop Prediction
We describe a new sampling-based algorithm, called CL-RRT#, which leverages ideas from the RRT# algorithm and a variant of the RRT algorithm that generates trajectories using closed-loop prediction.
Robotics
