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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 ...

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 ...

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 ...

The collective behavior of animals has been traditionally studied through observation, quantitative models of behavior, and devices of low intelligence. Nowadays, the advancements in the field of robotics allow for closed-loop experiments that occur in rea ...

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

In educational HRI, it is generally believed that a robots behavior has a direct effect on the engagement of a user with the robot, the task at hand and also their partner in case of a collaborative activity. Increasing this engagement is then held respons ...

The development of miniaturized machines that can actively cross barriers, navigate through heterogeneous materials and access remote sites can revolutionize environmental inspection and targeted therapy. Seminal work demonstrated the feasibility of follow ...

Adaptability and ease of programming are key features necessary for a wider spread of robotics in factories and everyday assistance. Learning from demonstration (LfD) is an approach to address this problem. It aims to develop algorithms and interfaces such ...

The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning per ...

In distributed optimization, parameter updates from the gradient computing node devices have to be aggregated in every iteration on the orchestrating server. When these updates are sent over an arbitrary commodity network, bandwidth and latency can be limi ...

Thought insertion (TI) is characterized by the experience that certain thoughts, occurring in one’s mind, are not one’s own, but the thoughts of somebody else and suggestive of a psychotic disorder. We report a robotics-based method able to investigate the ...

The use of robots in search and rescue is gaining particular interest, but singular skills are required to ensure efficient deployments in real missions. To face this problem, there is a need to develop more intuitive control interfaces. Moreover, to ensur ...

It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of “Inqu ...

Most policy search algorithms require thousands of training episodes to find an effective policy, which is often infeasible with a physical robot. This survey article focuses on the extreme other end of the spectrum: how can a robot adapt with only a handf ...

Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

The Robots for Learning workshop series aims at advancing the research topics related to the use of social robots in educational contexts. This year's half-day workshop follows on previous events in Human-Robot Interaction conferences focusing on efforts t ...

Robotics provides useful tools for educational purposes, allowing to engage students in learning within disparate domains, from computer science and artificial intelligence – traditionally the main domains for educational robotics – to general education, h ...

In this thesis our research goal is to develop, study and demonstrate multifunctional multi-robot systems in mesoscale. Particularly, our goal is to study and demonstrate terrestrial multi-locomotion and collective behaviours with mesoscale robots, similar ...

Robots are steadily becoming one of the significant 21st century learning technologies that aim to improve education within both formal and informal environments. Such robots, called Robots for Learning, have so far been utilized as constructionist tools o ...

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

Learning and optimization of anticipatory feedback controllers for robot manipulation

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

A biohybrid interaction framework for the integration of robots in animal societies

Memory of Motion for Initializing Optimization in Robotics

What if Social Robots look for Productive Engagement?

A Social Robot That Looks For Productive Engagement

Development of soft microscopic implants and acoustically-powered machines for biomedical applications

Product of experts for robot learning from demonstration

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Thought consciousness and source monitoring depend on robotically-controlled sensorimotor conflicts and illusory states

Wearable and Self-Aware Machine Learning System for Online Cognitive Workload Monitoring and Drone Control

Inquiry-Based Learning with RoboGen: An Open-Source Software and Hardware Platform for Robotics and Artificial Intelligence

A survey on policy search algorithms for learning robot controllers in a handful of trials

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Robots for Learning - R4L: Adaptive Learning

Robot swarms as an educational tool: The Thymio’s way

Design Methodology for Engineering Multifunctional Mesoscale Robots

Cellulo: Tangible Haptic Swarm Robots for Learning