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Found 4 papers, 1 papers with code
Progressive Smoothing for Motion Planning in Real-Time NMPC
Nonlinear model predictive control (NMPC) is a popular strategy for solving motion planning problems, including obstacle avoidance constraints, in autonomous driving applications.
Frenet-Cartesian Model Representations for Automotive Obstacle Avoidance within Nonlinear MPC
We specify costs and collision avoidance constraints in the more advantageous coordinate frame, derive appropriate formulations and compare different obstacle constraints.
Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots
The development of fast and safe approximate NMPC holds the potential to accelerate the adoption of flexible robots in industry.
An Inverse Optimal Control Approach for Trajectory Prediction of Autonomous Race Cars
The algorithm therefore learns to predict the observed vehicle trajectory in a least-squares relation to measurement data and to the presumed structure of the predicting NLP.
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