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A GPU-based solver for trajectory planning problems using branch model predictive control is presented. The solver is based on iterative LQR, multiple-shooting formulation, and augmented Lagrangian method for constraint handling. Numerical experiments show superiority over a CPU-based solver on large-scale problems.
Why it matters
Accelerating MPC computations on GPU enables real-time planning for large systems, which is critical for autonomous vehicles and robotics.
arXiv:2610.20041v1 Announce Type: cross Abstract: A staged physics-informed neural network (PINN) is proposed for identifying the inductance, capacitance and parasitic resistances of a DC buck converter from time-domain data.
arXiv:2610.18361v1 Announce Type: new Abstract: Real-time control systems may experience sporadic computational overloads that cause controller executions to overrun their expected deadlines, affecting the timely update of control inputs.
arXiv:2610.18400v1 Announce Type: new Abstract: Data trading markets that span industries and regions are expanding, but the implicit trust that supports data use within an organization does not carry over to cross-domain exchange.
