activity
20182022
most citedRoboCup 2019 AdultSize Winner NimbRo: Deep Learning Perception, In-Walk Kick, Push Recovery, and Team Play Capabilities

15 citations · 17 across the 3 of their papers we have counts for

collaborators

10 papers

cs.RO20222 cited

Co-Training an Observer and an Evading Target

André Brandenburger, Folker Hoffmann, Alexander Charlish

Reinforcement learning (RL) is already widely applied to applications such as robotics, but it is only sparsely used in sensor management. In this paper, we apply the popular Proxi…

cs.RO2021

Mapless Humanoid Navigation Using Learned Latent Dynamics

Andre Brandenburger, Diego Rodriguez, Sven Behnke

In this paper, we propose a novel Deep Reinforcement Learning approach to address the mapless navigation problem, in which the locomotion actions of a humanoid robot are taken onli…

cs.RO2020

NimbRo-OP2X: Affordable Adult-sized 3D-printed Open-Source Humanoid Robot for Research

Grzegorz Ficht, Hafez Farazi, Diego Rodriguez +4

For several years, high development and production costs of humanoid robots restricted researchers interested in working in the field. To overcome this problem, several research gr…

cs.RO201915 cited

RoboCup 2019 AdultSize Winner NimbRo: Deep Learning Perception, In-Walk Kick, Push Recovery, and Team Play Capabilities

Diego Rodriguez, Hafez Farazi, Grzegorz Ficht +7

Individual and team capabilities are challenged every year by rule changes and the increasing performance of the soccer teams at RoboCup Humanoid League. For RoboCup 2019 in the Ad…

cs.RO2019

NimbRo Robots Winning RoboCup 2018 Humanoid AdultSize Soccer Competitions

Hafez Farazi, Grzegorz Ficht, Philipp Allgeuer +5

Over the past few years, the Humanoid League rules have changed towards more realistic and challenging game environments, which encourage teams to advance their robot soccer perfor…

cs.RO2018

NimbRo-OP2X: Adult-sized Open-source 3D Printed Humanoid Robot

Grzegorz Ficht, Hafez Farazi, André Brandenburger +5

Humanoid robotics research depends on capable robot platforms, but recently developed advanced platforms are often not available to other research groups, expensive, dangerous to o…