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AccelMPC: High-Rate, Low-Power FPGA-Accelerated Model Predictive Control for Tiny Drones

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Unlocking the potential of tiny aerial robots requires order of magnitude improvements in the performance of embedded edge control. In particular, although recent cached model predictive control (MPC) solvers can handle the fast system dynamics and complex constraints required for agile drone flight, their computational demands remain prohibitive for resource-constrained robots, forcing prior implementations to operate at reduced control rates. AccelMPC overcomes this challenge through an end-to-end co-design approach that jointly optimizes the solver algorithm, numerical representation, hardw

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