Horse-like walking, trotting, and galloping derived from kinematic Motion Primitives (kMPs) and their application to walk/trot transitions in a compliant quadruped robot

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Participatory design of a social robot and robot-mediated storytelling activity to raise awareness of gender inequality among children

Barbara Bruno

Gender inequality is a widespread problem in our society. It can manifest itself in many ways and contexts, and starting as early as primary school. While an increasing number of initiatives aim at tackling gender biases and inequalities, few of them are a ...

IEEE2023

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

José del Rocio Millán Ruiz, Aude Billard, Fumiaki Iwane

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 ...

Nature Portfolio2023

Self-Correcting Quadratic Programming-Based Robot Control

Aude Billard, Farshad Khadivar, Konstantinos Chatzilygeroudis

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 ...

2023

Morphological flexibility in robotic systems through physical polygon meshing

Jamie Paik, Christoph Heinrich Belke, Kevin Andrew Holdcroft

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 ...

Nature Portfolio2023

Multi-robot task allocation for safe planning against stochastic hazard dynamics

Maryam Kamgarpour

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot optimal control pol ...

IEEE2023

Computational Models of Mutual Understanding for Human-Robot Collaborative Learning

Utku Norman

There is a growing trend towards designing learning activities featuring robots as collaborative exercises where children work together to achieve the activity objectives, generating interactions that can trigger learning processes. Witnessing such activit ...

EPFL2023

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Aude Billard, Harshit Khurana

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approa ...

IEEE2023

Reinforcement learning for scaffold-free construction of spanning-structures

Maryam Kamgarpour, Stefana Parascho, Anna Maria Maddux, Gabriel Rémi Vallat, Jingwen Wang

In construction robotics, a conventional design-to-fabrication work-flow starts with designing a structure, followed by task and robotic motion planning, and ultimately, fabrication. However, this approach can prove unsuccessful, as we may only discover th ...

New York2023

Motion Planning and Inertia Based Control for Impact Aware Manipulation

Aude Billard, Harshit Khurana

In this paper, we propose a metric called hitting flux which is used in the motion generation and controls for a robot manipulator to interact with the environment through a hitting or a striking motion. Given the task of placing a known object outside of ...

2023

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

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 ...

NATURE PORTFOLIO2023

Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Vaios Papaspyros

As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

EPFL2023