Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

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Robots outside of the fenced factories have to deal with continuously changing environment, this requires fast and flexible modes of control. Planning methods or complex learning models can find optimal paths in complex surroundings, but they are computati ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

Scattering wave systems that are periodically modulated in time offer many new degrees of freedom to control waves in both the spatial and frequency domains. Such systems, albeit linear, do not conserve frequency and require the adaptation of the usual the ...

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

Silicon Nitride (Si3N4) photonic integrated circuits (PICs) have emerged as core technology in a variety of applications ranging from LIDAR to quantum control and computing. However, the need for high-speed, low-voltage tuning and modulation has been a lon ...

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

Access to metal-organic frameworks (MOFs) with enhanced me-chanical stability is key to their successful deployment in practical applications. However, the high porosity of the material often af-fects mechanical stability. In this article, to achieve highl ...

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

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 ...

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 ...

A photochemical [2+2] cycloaddition of alkynyl boronates and maleimides is reported. The developed protocol provided 35–70 % yield of maleimide-derived cyclobutenyl boronates and demonstrated wide compatibility with various functional groups. The synthetic ...

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 ...

A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

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 ...

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

The integration of technology in the medical field has greatly improved accuracy in diagnoses, thus leading to more effective treatments. Wearable and implantable medical devices offer great potential for remote patient monitoring, particularly for heart f ...

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 ...

Crosstalk between fluorescent biomarkers significantly limits the resolution of multispectral fluorescence analysis in real-time droplet-microfluidics applications. The crosstalk is a result of overlapping emission and excitation spectra of different fluor ...

Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

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Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

Stability: a search for structure

The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Scattering from Time-Modulated Transmission-Line Loads: Theory and Experiments in Acoustics

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

Implicit Distance Functions: Learning and Applications in Robotics

Programmable Silicon Nitride Photonic Integrated Circuits

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks

Identifying important sensory feedback for learning locomotion skills

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

Self-Correcting Quadratic Programming-Based Robot Control

Photochemical [2+2] Cycloaddition of Alkynyl Boronates

Neuromechanical Simulations of Animats with Decentralised Control

Haptics based collaborative steering control in automated driving environments

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Integrated Electronics for Deep Implants to Remotely Monitor Hemodynamics

Training Efficient Controllers via Analytic Policy Gradient

Fluorescence crosstalk reduction by modulated excitation-synchronous acquisition for multispectral analysis in high-throughput droplet microfluidics