What if Social Robots look for Productive Engagement?

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Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

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 ...

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where the collaborative efforts of "simple" individuals can lead to the emergence of complex dynamics. The reliance of each organism on the collective is so great t ...

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 ...

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 ...

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 ...

This paper builds up the skill of impact aware non prehensile manipulation through a hitting motion by allowing the robot arm to come in contact with the environment with parts other than its end effector. Hitting with other joints allows us to manipulate ...

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 ...

Robotics is entering our daily lives. The discipline is increasingly crucial in fields such as agriculture, medicine, and rescue operations, impacting our food, health, and planet. At the same time, it is becoming evident that robotic research must embrace ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where collaboration and division of labor enhance survival of the whole colony, and are thus considered “superorganisms”. Historically, studying behaviors involving ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Harmful chemical compounds are released daily in warehouses, chemical plants and during environmental emergencies. Their uncontrolled dispersion contributes to the pollution of the atmosphere and threatens human and animal lives. When gas leaks occur, the ...

This doctoral thesis navigates the complex landscape of motion coordination and formation control within teams of rotary-wing Micro Aerial Vehicles (MAVs). Prompted by the intricate demands of real-world applications such as search and rescue or surveillan ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

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 ...

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

What if Social Robots look for Productive Engagement?

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Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Memento Mori: Reliable robustness in self-reconfigurable modular robots

A Biohybrid Superorganism - Investigating honeybees' collective behaviors via interactive robotics

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

Robot Learning using Tensor Networks

Investigating neural resource allocation in the sensorimotor control of extra limbs

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Hitting with Different Joints of a Robotic Manipulator

Online Multicontact Receding Horizon Planning via Value Function Approximation

Soft Robotics: A Route to Equality, Diversity, and Inclusivity in Robotics

Data and scripts for the RaFSIP scheme

Biohybrid Superorganisms—On the Design of a Robotic System for Thermal Interactions With Honeybee Colonies

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Gas Sensing with Rotary-Wing Nano Aerial Vehicles

Distributed Predictive Formation Control of Autonomous Rotary-Wing Micro Aerial Vehicles

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Small-scale robotic devices for medical interventions in the brain

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

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Robust machine learning for neuroscientific inference