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Found 5 papers, 3 papers with code
Do No Harm: A Counterfactual Approach to Safe Reinforcement Learning
In such methods, if agents are initialized in, or must visit, states where constraint violation might be inevitable, it is unclear how much they should be penalized.
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.
Guaranteed Safe Reachability-based Trajectory Design for a High-Fidelity Model of an Autonomous Passenger Vehicle
Trajectory planning is challenging for autonomous cars since they operate in unpredictable environments with limited sensor horizons.
Systems and Control
Bridging the Gap Between Safety and Real-Time Performance in Receding-Horizon Trajectory Design for Mobile Robots
At runtime, the FRS is used to map obstacles to the space of parameterized trajectories, which allows RTD to select a safe trajectory at every planning iteration.
Robotics Systems and Control
Safe Trajectory Synthesis for Autonomous Driving in Unforeseen Environments
Path planning for autonomous vehicles in arbitrary environments requires a guarantee of safety, but this can be impractical to ensure in real-time when the vehicle is described with a high-fidelity model.
Systems and Control Robotics
