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20212026
most citedReal-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms

222 citations · 250 across the 11 of their papers we have counts for

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11 papers · 1 filter

cs.RO2026

End-to-end QP-based policies: A unified perspective on robust control and robot learning

Fausto Vega, Priyanka Supraja Balaji, Chase Dunaway +3

We present an end-to-end QP-based policy framework that enables systematic policy construction with minimal domain-specific design, while preserving the transparency and interpreta…

cs.RO2026

Fast and Robust Temporal Logic Planning via ADMM-based Trajectory Optimization

Lukas Pries, Joris Verhagen, Jon Arrizabalaga +3

We present a fast numerical method for safe continuous-time motion planning under Temporal Logic (TL) specifications. The method generates smooth continuous trajectories that remai…

cs.RO2026

ADMM-based Continuous Trajectory Optimization in Graphs of Convex Sets

Lukas Pries, Jon Arrizabalaga, Zachary Manchester +1

This paper presents a numerical solver for computing continuous trajectories in non-convex environments. Our approach relies on a customized implementation of the Alternating Direc…

cs.RO2024

PHODCOS: Pythagorean Hodograph-based Differentiable Coordinate System

Jon Arrizabalaga, Fausto Vega, Zbyněk ŠÍR +2

This paper presents PHODCOS, an algorithm that assigns a moving coordinate system to a given curve. The parametric functions underlying the coordinate system, i.e., the path functi…

cs.RO2024★ 1 cited

A Universal Formulation for Path-Parametric Planning and Control

Jon Arrizabalaga, Zbyněk ŠÍR, Zachary Manchester +1

We present a unified framework for path-parametric planning and control. This formulation is universal as it standardizes the entire spectrum of path-parametric techniques -- from…

cs.RO2024★ 1 cited

Differentiable Collision-Free Parametric Corridors

Jon Arrizabalaga, Zachary Manchester, Markus Ryll

This paper presents a method to compute differentiable collision-free parametric corridors. In contrast to existing solutions that decompose the obstacle-free space into multiple c…

cs.RO2024

Geometric Slosh-Free Tracking for Robotic Manipulators

Jon Arrizabalaga, Lukas Pries, Riddhiman Laha +3

This work focuses on the agile transportation of liquids with robotic manipulators. In contrast to existing methods that are either computationally heavy, system/container specific…

cs.RO2023

Pose-Following with Dual Quaternions

Jon Arrizabalaga, Markus Ryll

This work focuses on pose-following, a variant of path-following in which the goal is to steer the system's position and attitude along a path with a moving frame attached to it. F…

cs.RO2022

SCTOMP: Spatially Constrained Time-Optimal Motion Planning

Jon Arrizabalaga, Markus Ryll

This paper focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows the system to plan within a predefined spa…

cs.RO2022★ 222 cited

Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms

Tim Salzmann, Elia Kaufmann, Jon Arrizabalaga +3

Model Predictive Control (MPC) has become a popular framework in embedded control for high-performance autonomous systems. However, to achieve good control performance using MPC, a…

cs.RO2021★ 19 cited

Towards Time-Optimal Tunnel-Following for Quadrotors

Jon Arrizabalaga, Markus Ryll

Minimum-time navigation within constrained and dynamic environments is of special relevance in robotics. Seeking time-optimality, while guaranteeing the integrity of time-varying s…