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Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics

Related publications (32)

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Josephine Anna Eleanor Hughes, Francesco Stella

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system' ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Aude Billard, Harshit Khurana

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approa ...

IEEE2023

Bimanual dynamic grabbing and tossing of objects onto a moving target

Aude Billard, Michael Bosongo Bombile

Bimanual grabbing and tossing of packages onto trays or conveyor belts remains a human activity in the industry. For robots, such a dynamic task requires coordination between two arms and fast adaptation abilities when the tossing target is moving and subj ...

Elsevier2023

Self-Correcting Quadratic Programming-Based Robot Control

Aude Billard, Konstantinos Chatzilygeroudis, Farshad Khadivar

Quadratic Programming (QP)-based controllers allow many robotic systems, such as humanoids, to successfully undertake complex motions and interactions. However, these approaches rely heavily on adequately capturing the underlying model of the environment a ...

2023

Morphological flexibility in robotic systems through physical polygon meshing

Jamie Paik, Christoph Heinrich Belke, Kevin Andrew Holdcroft, Alexander Thomas Sigrist

Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

Nature Portfolio2023

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hakan Girgin

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach

Olga Fink, Sergei Garmaev

With the current trend of increasing complexity of industrial systems, the construction and monitoring of health indicators becomes even more challenging. Given that health indicators are commonly employed to predict the end of life, a crucial criterion fo ...

Research Publishing2023

Neuromechanical Simulations of Animats with Decentralised Control

Jonathan Patrick Arreguit O'Neill

The transition from aquatic to terrestrial environments represents a significant event in the history of evolution. For this transition to occur, animals had to adapt their morphology, physiology and locomotory skills to handle the challenges and interacti ...

EPFL2023

Online active and dynamic object shape exploration with a multi-fingered robotic hand

Aude Billard, Kunpeng Yao, Farshad Khadivar, Xiao Gao

The sense of touch can provide a robot with a wealth of information about the contact region when interacting with an unknown environment. Nevertheless, utilizing touch information to plan exploration paths and adjust robot posture to improve task efficien ...

Elsevier2023

Error scaling laws for kernel classification under source and capacity conditions

Hugo Chao Cui, Florent Gérard Krzakala, Lenka Zdeborová, Bruno Loureiro, Bruno Loureiro

In this manuscript we consider the problem of kernel classification. While worst-case bounds on the decay rate of the prediction error with the number of samples are known for some classifiers, they often fail to accurately describe the learning curves of ...

2023

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Christian Robert Abbet

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

EPFL2023