222 citations · 371 across the 19 of their papers we have counts for
20 papers
Optimal Control with Learned Critics under Unmodeled State Dependencies
Philipp Schoch, Markus Ryll
Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analytical dynamics models limits…
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…
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…
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…
Dual Quaternion Control of UAVs with Cable-suspended Load
Yuxia Yuan, Markus Ryll
Modeling the kinematics and dynamics of robotics systems with suspended loads using dual quaternions has not been explored so far. This paper introduces a new innovative control st…
Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection
Tim Salzmann, Markus Ryll, Alex Bewley +1
Visual relationship detection aims to identify objects and their relationships in images. Prior methods approach this task by adding separate relationship modules or decoders to ex…
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…
Learning for CasADi: Data-driven Models in Numerical Optimization
Tim Salzmann, Jon Arrizabalaga, Joel Andersson +2
While real-world problems are often challenging to analyze analytically, deep learning excels in modeling complex processes from data. Existing optimization frameworks like CasADi…
Robots That Can See: Leveraging Human Pose for Trajectory Prediction
Tim Salzmann, Lewis Chiang, Markus Ryll +3
Anticipating the motion of all humans in dynamic environments such as homes and offices is critical to enable safe and effective robot navigation. Such spaces remain challenging as…
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…
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…
Spatial motion planning with Pythagorean Hodograph curves
Jon Arrizabalaga, Markus Ryll
This paper presents a two-stage prediction-based control scheme for embedding the environment's geometric properties into a collision-free Pythagorean Hodograph spline, and subsequ…
Visual Navigation for Autonomous Vehicles: An Open-source Hands-on Robotics Course at MIT
Luca Carlone, Kasra Khosoussi, Vasileios Tzoumas +5
This paper reports on the development, execution, and open-sourcing of a new robotics course at MIT. The course is a modern take on "Visual Navigation for Autonomous Vehicles" (VNA…
SMORS: A soft multirotor UAV for multimodal locomotion and robust interaction
Markus Ryll, Robert K. Katzschmann
We present SMORS, the first Soft fully actuated MultirOtoR System for multimodal locomotion. Unlike conventional hexarotors, SMORS is equipped with three rigid and three continuous…
Motron: Multimodal Probabilistic Human Motion Forecasting
Tim Salzmann, Marco Pavone, Markus Ryll
Autonomous systems and humans are increasingly sharing the same space. Robots work side by side or even hand in hand with humans to balance each other's limitations. Such cooperati…
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…
A caster-wheel-aware MPC-based motion planner for mobile robotics
Jon Arrizabalaga, Niels van Duijkeren, Markus Ryll +1
Differential drive mobile robots often use one or more caster wheels for balance. Caster wheels are appreciated for their ability to turn in any direction almost on the spot, allow…
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…
FAST-Hex -- A Morphing Hexarotor: Design, Mechanical Implementation, Control and Experimental Validation
Markus Ryll, Davide Bicego, Mattia Giurato +2
We present FAST-Hex, a micro aerial hexarotor platform that allows to seamlessly transit from an under-actuated to a fully-actuated configuration with only one additional control i…
Full-Pose Tracking Control for Aerial Robotic Systems with Laterally-Bounded Input Force
Antonio Franchi, Ruggero Carli, Davide Bicego +1
In this paper, we define a general class of abstract aerial robotic systems named Laterally Bounded Force (LBF) vehicles, in which most of the control authority is expressed along…