System Identification of Self-Organizing Robotic Swarms

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We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Dielectric Elastomer Actuators (DEAs) have emerged as versatile and promising devices for a multitude of applications, including soft robotics, haptic interfaces, and artificial muscles. DEAs are an interesting soft actuator technology due to their high en ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

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 ...

In recent years, exploring deep generative models for generating time series has garnered significant interest within the research community. These models have found wide-ranging applications in areas such as data augmentation, scenario simulation, and the ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

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 ...

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' ...

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

Haptic perception of softness is a unique feature of the human skin that relies on the concurrent measurements of the lateral deformation and compression of the skin during object manipulation. This is challenging to implement in robotics because of combin ...

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

Aquatic creatures exhibit remarkable adaptations of their body to efficiently interact with the surrounding fluid. The tight coupling between their morphology, motion, and the environment are highly complex but serves as a valuable example when creating bi ...

Soft robots aim to revolutionize how robotic systems interact with the environment thanks to their inherent compliance. Some of these systems are even able to modulate their physical softness. However, simply equipping a robot with softness will not genera ...

System Identification of Self-Organizing Robotic Swarms

Chattez avec Graph Search

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Frequency response of fiber reinforced DEAs

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Morphological flexibility in robotic systems through physical polygon meshing

One-Pass Generation of Multivariate Time Series through Conditional Multivariate Modeling

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Learning and optimization of anticipatory feedback controllers for robot manipulation

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Liquid Metal-Based Sensor Skin Enabling Haptic Perception of Softness

3D printed large amplitude torsional microactuators powered by ultrasound

Efficient and insightful descriptors for representing molecular and material space

Training Efficient Controllers via Analytic Policy Gradient

Control and Morphology Optimization of Passive Asymmetric Structures for Robotic Swimming

Prescribing Cartesian Stiffness of Soft Robots by Co-Optimization of Shape and Segment-Level Stiffness