Platform game | EPFL Graph Search

A platform game (often simplified as platformer and sometimes called a jump 'n' run game) is a sub-genre of action video games in which the core objective is to move the player character between points in an environment. Platform games are characterized by levels that consist of uneven terrain and suspended platforms of varying height that require jumping and climbing to traverse. Other acrobatic maneuvers may factor into the gameplay, such as swinging from vines or grappling hooks, jumping off walls, air dashing, gliding through the air, being shot from cannons, or bouncing from springboards or trampolines. Games where jumping is automated completely, such as 3D games in The Legend of Zelda series, fall outside of the genre. The genre started with the 1980 arcade video game, Space Panic, which includes ladders, but not jumping. Donkey Kong, released in 1981, established a template for what were initially called "climbing games." Donkey Kong inspired many clones and games with simi

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

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

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 sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain-body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 "Neurorobotics" of the Human Brain Project (HBP). 1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.

2017

Exploration of micro-acoustic spectrometry techniques

Florian Fernand Hartmann

This master’s thesis aimed at exploring the field of micro-acoustic spectrometry using surface acoustic waves. The objectives of this project were to design and fabricate a platform for the detection and characterization of bioentities. Design of a delay line based on the experience and knowledge of the ANEMS group and on investigation of existing solutions was performed. Different configurations and types of transducers were simulated to come up with some meaningful designs for fabrication. The devices were fabricated in the clean rooms at EPFL with a specific process flow used for the suspended structures. Extensive simulation of bidirectional and unidirectional transducers were carried out in order to understand their behavior and to be able to use them as the elements of the sensing platform. Setbacks prevented the completion of the fabrication and no real measurements could be done before the end of this project, but the simulations gave nice perspectives for the targeted application. The potential of surface acoustic waves to detect modifications in the elasticity or the density of a material could be witnessed in the last simulations.

2022

Cellulo: Versatile Handheld Robots for Education

Maria Maria Beltran Reyes, Wafa Monia Benkaouar Johal, Manon Aline Briod, Pierre Dillenbourg, Séverin Lemaignan, Francesco Mondada, Ayberk Özgür, Léa Marie Pereyre

In this article, we present Cellulo, a novel robotic platform that investigates the intersection of three ideas for robotics in education: designing the robots to be versatile and generic tools; blending robots into the classroom by designing them to be pervasive objects and by creating tight interactions with (already pervasive) paper; and finally considering the practical constraints of real classrooms at every stage of the design. Our platform results from these considerations and builds on a unique combination of technologies: groups of handheld haptic-enabled robots, tablets and activity sheets printed on regular paper. The robots feature holonomic motion, haptic feedback capability and high accuracy localization through a microdot pattern overlaid on top of the activity sheets, while remaining affordable (robots cost about EUR 125 at the prototype stage) and classroom-friendly. We present the platform and report on our first interaction studies, involving about 230 children.

ACM2017

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

2017