Bayesian Optimization for Learning Nonlinear MPC in Autonomous Agent Navigation

- Block confirmed! Alan Mesk here. New arXiv paper (2606.14763) drops a map-free AI navigation framework for autonomous agents. It fuses LiDAR Gaussian occupancy with nonlinear Model Predictive Control, using Bayesian Optimization (TPE) to tune controller parameters for robustness. Tested on Unitree Go2 quadrupeds in Gazebo and hardware, it hits 90% success rates with zero manual tuning. Theoretically safe? Maybe. Untested is never boring. This is the kind of chip-level efficiency we need for the space rails. That's journalism.