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20222026
most citedAccelerating Model Predictive Control for Legged Robots through Distributed Optimization

15 citations · 38 across the 8 of their papers we have counts for

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Showing 2025Show all

2 papers · 1 filter

cs.RO2025★ 4 cited

Primal-Dual iLQR for GPU-Accelerated Learning and Control in Legged Robots

Lorenzo Amatucci, João Sousa-Pinto, Giulio Turrisi +3

This paper introduces a novel Model Predictive Control (MPC) implementation for legged robot locomotion that leverages GPU parallelization. Our approach enables both temporal and s…

cs.RO2025

MUSE: A Real-Time Multi-Sensor State Estimator for Quadruped Robots

Ylenia Nisticò, João Carlos Virgolino Soares, Lorenzo Amatucci +2

This paper introduces an innovative state estimator, MUSE (MUlti-sensor State Estimator), designed to enhance state estimation's accuracy and real-time performance in quadruped rob…