A Biologically-Inspired Model of Reaching Movements

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Modular robotics link the reliability of a centralised system with the adaptivity of a decentralised system. It is difficult for a robot with a fixed shape to be able to perform many different types of tasks. As the task space grows, the number of functi ...

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 various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

Given the patchy nature of gas plumes and the slow response of conventional gas sensors, the use of mobile robots for Gas Source Localization (GSL) tasks presents significant challenges. These aspects increase the difficulties in obtaining gas measurements ...

Planning multicontact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditionally, the value function is approximated by computing traj ...

Controlling complex tasks in robotic systems, such as circular motion for cleaning or following curvy lines, can be dealt with using nonlinear vector fields. This article introduces a novel approach called the rotational obstacle avoidance method (ROAM) fo ...

In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulatio ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

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 ...

Dynamic modeling of folding joints is critical for predicting dynamic behavior, optimizing design parameters, and developing control strategies for origami robots and machines. Although kinematics of the folded joints exists, little research describes thei ...

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 ...

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 ...

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 ...

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 ...

The digitization of timber construction, the emergence of engineered wood products, and the urgent need to drastically reduce buildings' environmental impact have given a rebirth to wood as a construction material. On the one hand, increasing the use of ti ...

Myoelectric prostheses allow users to recover lost functionality by controlling a robotic device with their remaining muscle activity. Commercial devices usually use a two-recording-channel system placed on specific muscles to control a single degree of fr ...

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 ...

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 ...

A Biologically-Inspired Model of Reaching Movements

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Memento Mori: Reliable robustness in self-reconfigurable modular robots

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

Robot Learning using Tensor Networks

Sense in Motion with Belief Clustering: Efficient Gas Source Localization with Mobile Robots

Online Multicontact Receding Horizon Planning via Value Function Approximation

Avoidance of Concave Obstacles Through Rotation of Nonlinear Dynamics

Geometric Learning: Leveraging differential geometry for learning and control

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Investigating neural resource allocation in the sensorimotor control of extra limbs

Exploration-based model learning with self-attention for risk-sensitive robot control

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

Dynamic Modeling of an Origami Prismatic Joint

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Morphological flexibility in robotic systems through physical polygon meshing

Self-Correcting Quadratic Programming-Based Robot Control

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

Robotic Assembly of Integrally-Attached Timber Plate Structures: From Computational Design to Automated Construction

Improving hand prosthesis control with advanced single-finger proportional decoding and robotic shared control

Control and Morphology Optimization of Passive Asymmetric Structures for Robotic Swimming

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