Publications related to Evolutionary robotics

VP-STO: Via-point-based Stochastic Trajectory Optimization for Reactive Robot Behavior

Sylvain Calinon, Julius Maximilian Jankowski

Achieving reactive robot behavior in complex dynamic environments is still challenging as it relies on being able to solve trajectory optimization problems quickly enough, such that we can replan the future motion at frequencies which are sufficiently high ...

IEEE2023

Multi-Source Fusion for Voxel-Based 7-DoF Grasping Pose Estimation

Zheng Dang, Fei Wang

In this work, we tackle the problem of 7-DoF grasping pose estimation(6-DoF with the opening width of parallel-jaw gripper) from point cloud data, which is a fundamental task in robotic manipulation. Most existing methods adopt 3D voxel CNNs as the backbon ...

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

A Muscle-Reflex Model of Forelimb and Hindlimb of Felidae Family of Animal with Dynamic Pattern Formation Stimuli

Auke Ijspeert, Azhar Aulia Saputra

Human and animal locomotion are controlled by complex neural circuits, which can also serve as inspiration for designing locomotion controllers for dynamic locomotion in legged robots. We develop a locomotion controller model including a central pattern ge ...

IEEE2020

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

Dario Floreano, Joshua Evan Auerbach, Przemyslaw Mariusz Kornatowski, Alice Ghislaine Concordel

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 ...

2019

Collision Avoidance with Limited Field of View Sensing: A Velocity Obstacle Approach

Denis Gillet, Alcherio Martinoli, Steven Adriaan Roelofsen

Collision avoidance, in particular between robots, is an important component for autonomous robots. It is a necessary component in numerous applications such as human-robot interaction, automotive or unmanned aerial vehicles. While many collision avoidance ...

2017

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Daniel Peppicelli, Marc-Oliver Gewaltig, Luc Guyot, Egidio Falotico, Lorenzo Vannucci, Axel von Arnim, Paul Levi, Georg Hinkel, Stefan Ulbrich, Eduardo Ros, Alessandro Ambrosano, Nino Cauli, Patrick Van Der Smagt, Oliver Denninger, Ugo Albanese, Murat Kirtay, Stefan Deser, Sandro Weber, Patrick Maier, Igor Peric

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensor ...

2017

Noise-Resistant Particle Swarm Optimization for the Learning of Robust Obstacle Avoidance Controllers using a Depth Camera

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

The Ranger robot was designed to interact with children in order to motivate them to tidy up their room. Its mechanical configuration, together with the limited field of view of its depth camera, make the learning of obstacle avoidance behaviors a hard pro ...

Ieee2016

Rapid Evolution of Robot Gaits

Dario Floreano, Joshua Evan Auerbach, Przemyslaw Mariusz Kornatowski, Grégoire Hilaire Marie Heitz

The promise of Evolutionary Robotics (ER) to completely automatize the design of robot controllers and/or morphologies is an idea with great appeal not only to researchers, but also to students. However, when attempting to grab and hold student interest, t ...

ACM2015

A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

Population-based learning techniques have been proven to be effective in dealing with noise in numerical benchmark functions and are thus promising tools for the high-dimensional optimization of controllers for multiple robots with limited sensing capabili ...

2015

Distributed Particle Swarm Optimization - Particle Allocation and Neighborhood Topologies for the Learning of Cooperative Robotic Behaviors

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

In this article we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots, as a canonical example of cooperative robotic behavior. We use five distributed noise-resistant variations of Particle Swarm Optimizat ...

2015

Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

In this paper we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots. We use a noise-resistant version of Particle Swarm Optimization to learn in simulation a set of 50 weights of a plastic artificial neura ...

The MIT Press2015

RoboGen: Robot Generation through Artificial Evolution

Dario Floreano, Ilya Loshchilov, Joshua Evan Auerbach, Andrea Maesani, Ludovic Daler, Przemyslaw Mariusz Kornatowski, Titus Cieslewski, Grégoire Hilaire Marie Heitz, Deniz Aydin, Pradeep Ruben Fernando

Science instructors from a wide range of disciplines agree that hands-on laboratory components of courses are pedagogically necessary (Freedman, 1997). However, certain shortcomings of current laboratory exercises have been pointed out by several authors ( ...

The MIT Press2014

Distributed Learning of Cooperative Robotic Behaviors using Particle Swarm Optimization

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

In this paper we study the automatic synthesis of robotic controllers for the coordinated movement of multiple mobile robots. The algorithm used to learn the controllers is a noise-resistant version of Particle Swarm Optimization, which is applied in two d ...

2016

Evolution of division of labor in artificial societies

Pawel Lichocki

Natural and artificial societies often divide the workload between specialized members. For example, an ant worker may preferentially perform one of many tasks such as brood rearing, foraging and nest maintenance. A robot from a rescue team may specialize ...

EPFL2013

Historical contingency affects signaling strategies and competitive abilities in evolving populations of simulated robots

Dario Floreano, Laurent Keller

One of the key innovations during the evolution of life on earth has been the emergence of efficient communication systems, yet little is known about the causes and consequences of the great diversity within and between species. By conducting experimental ...

National Academy of Sciences2012

Imitation Learning of Motion Coordination in Robots : a Dynamical System Approach

Elena Gribovskaya

The ease with which humans coordinate all their limbs is fascinating. Such a simplicity is the result of a complex process of motor coordination, i.e. the ability to resolve the biomechanical redundancy in an efficient and repeatable manner. Coordination e ...

EPFL2012

Multi-level Spatial Modeling for Stochastic Distributed Robotic Systems

Alcherio Martinoli, Amanda Stella Markowska Prorok, Nicolaus Correll

We propose a combined spatial and non-spatial probabilistic modeling methodology motivated by an inspection task performed by a group of miniature robots. Our models explicitly consider spatiality and yield accurate predictions on system performance. An ag ...

2011

Towards Optimally Efficient Field Estimation with Threshold-Based Pruning in Real Robotic Sensor Networks

Alcherio Martinoli, Amanda Stella Markowska Prorok, Christopher Cianci

The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the problem of optimizing this trade-off in a self-configured distributed robotic sensor network ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Highly Compact Robots for Inspection of Power Plants

Francesco Mondada, Roland Siegwart, Roland Moser, Fabien Tâche, Frédéric Rochat, Gilles Caprari, Patrick Schoeneich, Andreas Breitenmoser

This paper reports on a 3 years applied research project dealing with several inspection scenarios of power plants and resulting in many robot prototypes and 3 main achievements. The project is a common effort between industry and university, including ALS ...

IEEE Press2010