activity
20162025
most citedLearning Whole-body Motor Skills for Humanoids

21 citations · 56 across the 17 of their papers we have counts for

collaborators
Showing 2022 · cs.ROShow all

5 papers · 2 filters

cs.RO2022

Learning and Deploying Robust Locomotion Policies with Minimal Dynamics Randomization

Luigi Campanaro, Siddhant Gangapurwala, Wolfgang Merkt +1

Training deep reinforcement learning (DRL) locomotion policies often require massive amounts of data to converge to the desired behaviour. In this regard, simulators provide a chea…

cs.RO2022★ 1 cited

VAE-Loco: Versatile Quadruped Locomotion by Learning a Disentangled Gait Representation

Alexander L. Mitchell, Wolfgang Merkt, Mathieu Geisert +5

Quadruped locomotion is rapidly maturing to a degree where robots are able to realise highly dynamic manoeuvres. However, current planners are unable to vary key gait parameters of…

cs.RO2022

Agile Maneuvers in Legged Robots: a Predictive Control Approach

Carlos Mastalli, Wolfgang Merkt, Guiyang Xin +4

Planning and execution of agile locomotion maneuvers have been a longstanding challenge in legged robotics. It requires to derive motion plans and local feedback policies in real-t…

cs.RO2022★ 2 cited

RoLoMa: Robust Loco-Manipulation for Quadruped Robots with Arms

Henrique Ferrolho, Vladimir Ivan, Wolfgang Merkt +2

Deployment of robotic systems in the real world requires a certain level of robustness in order to deal with uncertainty factors, such as mismatches in the dynamics model, noise in…

cs.RO2022★ 2 cited

Motion Planning in Dynamic Environments Using Context-Aware Human Trajectory Prediction

Mark Nicholas Finean, Luka Petrović, Wolfgang Merkt +2

Over the years, the separate fields of motion planning, mapping, and human trajectory prediction have advanced considerably. However, the literature is still sparse in providing pr…