Publications related to Distributed Scalable Multi-Robot Learning using Particle Swarm Optimization

A Distributed Source Term Estimation Algorithm for Multi-Robot Systems

Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, security, and emergency situations related to medical, domestic, and environmental domains. Given the often critical nature of all the applications, it is impor ...

2020

Being Part of the Swarm: Experiencing Human-Swarm Interaction with VR and Tangible Robots

Pierre Dillenbourg, Barbara Bruno, Arzu Güneysu Özgür, Kevin Gonyop Kim, Hala Khodr

A swarm is the coherent behavior that emerges ubiquitously fromsimple interaction rules between self-organized agents. Understand-ing swarms is of utmost importance in many disciplines and jobs,but hard to teach due to the elusive nature of the phenomenon, ...

2020

An Institutional Approach to Normative Distributed Robotics for Mixed Societies of Humans and Robots

Alicja Barbara Roelofsen

We are entering the era of robots, for everyone, everywhere. The expectations of the robots being reliable, intelligent and friendly artificial creatures drive the key challenges of the state-of-the-art robotics: technological, practical and social. The la ...

EPFL2020

Using tabletop robots to promote inclusive classroom experiences

Wafa Monia Benkaouar Johal, Arzu Güneysu Özgür, Ana Paiva

Geometry and handwriting rely heavily on the visual representation of basic shapes. It can become challenging for students with visual impairments to perceive these shapes and understand complex spatial constructs. For instance, knowing how to draw is high ...

ACM2020

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Sylvain Calinon, Emmanuel Pignat, Hakan Girgin, Noémie Laure Gwendoline Jaquier

Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In this pa ...

IEEE2020

Memory of Motion for Warm-Starting Trajectory Optimization

Sylvain Calinon, Emmanuel Pignat, Antonio Paolillo, Teguh Santoso Lembono

Trajectory optimization for motion planning requires good initial guesses to obtain good performance. In our proposed approach, we build a memory of motion based on a database of robot paths to provide good initial guesses. The memory of motion relies on f ...

2020

An optimized material removal process

Jean-François Molinari, Son-Jonathan Pham-Ba

We conduct boundary element simulations of a contact problem consisting of an elastic medium subject to tangential load. Using a particle swarm optimization algorithm, we find the optimal shape and location of the micro-contacts to maximize for a given loa ...

2020

Flexible, adaptive industrial assembly: driving innovation through competition

Josephine Anna Eleanor Hughes, Kieran Daniel Gilday

Robotics competitions stimulate the next generation of cutting edge robotics solutions and innovative technologies. The World Robot Summit (WRS) Industrial Assembly challenge posed a key research challenge: how to develop adaptive industrial assembly robot ...

Springer2020

Measurement Scheduling for Cooperative Localization in Resource-Constrained Conditions

Qi Yan, Li Jiang

This letter studies the measurement scheduling problem for a group of

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mobile robots moving on a flat surface that are preforming cooperative localization (CL). We consider a scenario in which due to the limited on-board resources such as battery life a ...

2020

Improving robotic cooking using batch bayesian optimization

Josephine Anna Eleanor Hughes, Kai Christian Junge

With advances in the field of robotic manipulation, sensing and machine learning, robotic chefs are expected to become prevalent in our kitchens and restaurants. Robotic chefs are envisioned to replicate human skills in order to reduce the burden of the co ...

Institute of Electrical and Electronics Engineers Inc.2020

Distributed Scalable Multi-Robot Learning using Particle Swarm Optimization

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A Distributed Source Term Estimation Algorithm for Multi-Robot Systems

Being Part of the Swarm: Experiencing Human-Swarm Interaction with VR and Tangible Robots

An Institutional Approach to Normative Distributed Robotics for Mixed Societies of Humans and Robots

Using tabletop robots to promote inclusive classroom experiences

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Memory of Motion for Warm-Starting Trajectory Optimization

An optimized material removal process

Flexible, adaptive industrial assembly: driving innovation through competition

Measurement Scheduling for Cooperative Localization in Resource-Constrained Conditions

Improving robotic cooking using batch bayesian optimization

An Institutional Approach to Normative Distributed Robotics for Mixed Societies of Humans and Robots

Being Part of the Swarm: Experiencing Human-Swarm Interaction with VR and Tangible Robots

A Distributed Source Term Estimation Algorithm for Multi-Robot Systems

Using tabletop robots to promote inclusive classroom experiences

Measurement Scheduling for Cooperative Localization in Resource-Constrained Conditions

Flexible, adaptive industrial assembly: driving innovation through competition

Memory of Motion for Warm-Starting Trajectory Optimization

Improving robotic cooking using batch bayesian optimization

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

An optimized material removal process