Publications related to Recognition and Reproduction of Gestures using a Probabilistic Framework combining PCA, ICA and HMM

Related publications (30)

Online Multicontact Receding Horizon Planning via Value Function Approximation

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 ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Robust machine learning for neuroscientific inference

Steffen Schneider

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 ...

EPFL2024

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

Lukas Huber

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 ...

EPFL2024

Implicit Distance Functions: Learning and Applications in Robotics

Mikhail Koptev

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 ...

EPFL2023

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

Scalable and Privacy-Preserving Federated Principal Component Analysis

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Joao André Gomes de Sá e Sousa, David Jules Froelicher, Jean-Philippe Léonard Bossuat

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Accessible Soft Robotics Education with Re-configurable Balloon Robots

Josephine Anna Eleanor Hughes, Kieran Daniel Gilday, Yi-Shiun Wu

Soft robotics requires effective tools to educate the next generation of engineers and researchers. Stemming from a lack of universally accepted principles for education and with high barriers to entry in terms of fabrication and hardware, education to dat ...

IEEE2023

Tales from a Robotic World. How Intelligent Machines Will Shape Our Future

Dario Floreano, Nicola Nosengo

Stories from the future of intelligent machines—from rescue drones to robot spouses—and accounts of cutting-edge research that could make it all possible. Tech prognosticators promised us robots—autonomous humanoids that could carry out any number of tasks ...

MIT Press2022

Advancing coordination control of multi-limb robotic tasks: application to bimanual dynamic manipulation and bipedal reactive locomotion

Michael Bosongo Bombile

Bi-manual picking up of objects to toss them on a conveyor belt are dynamic manipulation activities generated daily in the industry. Such repetitive and physically demanding tasks are still done largely by humans for lack of similarly fast, precise, and ro ...

EPFL2022

Autoencoders reloaded

Hervé Bourlard, Selen Hande Kabil

In Bourlard and Kamp (Biol Cybern 59(4):291-294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called "auto-associative multilayer perceptrons") were, in the best case, implementing singular value decomposit ...

SPRINGER2022

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Sylvain Calinon, Teguh Santoso Lembono

In this paper, we propose a framework to build a memory of motion for warm-starting an optimal control solver for the locomotion task of a humanoid robot. We use HPP Loco3D, a versatile locomotion planner, to generate offline a set of dynamically consisten ...

IEEE2020

Complexity and Similarity Metrics for Unsupervised Identification of Programming Methods for Robot Cooking Tasks

Josephine Anna Eleanor Hughes, Stefan Ilic

Using robotics to automate complex manipulation tasks such as cooking could offer significant advantages. Robotics could offer improved throughput, provide assistance for those that lack the required mobility or allow for creative robotic chefs. Generating ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Learning to Guide Online Multi-Contact Receding Horizon Planning

Sylvain Calinon, Teguh Santoso Lembono

In Receding Horizon Planning (RHP), it is critical that the motion being executed facilitates the completion of the task, e.g. building momentum to overcome large obstacles. This requires a value function to inform the desirability of robot states. However ...

IEEE2022

Learning (Good Handwriting In Greek) By Teaching (A Humanoid Robot)

Wafa Monia Benkaouar Johal, Thibault Lucien Christian Asselborn, Thanasis Hadzilacos

We report on a follow-up study of the Co-Writer project at EPFL [1]; we confirm their findings, extend the applicability to another language with a different alphabet (Greek) and go into an in-depth qualitative study of the child-robot relationship. The co ...

IATED-INT ASSOC TECHNOLOGY EDUCATION & DEVELOPMENT2020

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Bahar Radmehr, Tanja Christina Käser Jacober, Mirko Marras, Vinitra Swamy

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

2022

When Positive Perception of the Robot Has No Effect on Learning

Pierre Dillenbourg, Barbara Bruno, Jauwairia Nasir, Utku Norman

Humanoid robots, with a focus on personalised social behaviours, are increasingly being deployed in educational settings to support learning. However, crafting pedagogical HRI designs and robot interventions that have a real, positive impact on participant ...

IEEE2020

Learning from demonstration using products of experts: Applications to manipulation and task prioritization

Sylvain Calinon, Emmanuel Pignat

Probability distributions are key components of many learning from demonstration (LfD) approaches, with the spaces chosen to represent tasks playing a central role. Although the robot configuration is defined by its joint angles, end-effector poses are oft ...

2021

A Dynamical System Approach for Adaptive Grasping, Navigation and Co-Manipulation with Humanoid Robots

Aude Billard, Salman Faraji, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

In this paper, we present an integrated approach that provides compliant control of an iCub humanoid robot and adaptive reaching, grasping, navigating and co-manipulating capabilities. We use state-dependent dynamical systems (DS) to (i) coordinate and dri ...

IEEE2020

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Aude Billard, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

In this letter, we propose a real-time self-collision avoidance approach for whole-body humanoid robot control. To achieve this, we learn the feasible regions of control in the humanoid's joint space as smooth self-collision boundary functions. Collision-f ...

2021

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

Fabio Isidoro Tiberio Dell'Agnola

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 ...

EPFL2020