activity
20162025
most citedSafe and Compliant Control of Redundant Robots Using Superimposition of Passive Task-Space Controllers

22 citations · 126 across the 31 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.RO2021★ 1 cited

Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion

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

Quadruped locomotion is rapidly maturing to a degree where robots now routinely traverse a variety of unstructured terrains. However, while gaits can be varied typically by selecti…

cs.RO2021

Where Should I Look? Optimised Gaze Control for Whole-Body Collision Avoidance in Dynamic Environments

Mark Nicholas Finean, Wolfgang Merkt, Ioannis Havoutis

As robots operate in increasingly complex and dynamic environments, fast motion re-planning has become a widely explored area of research. In a real-world deployment, we often lack…

cs.RO2021

Rapid Convex Optimization of Centroidal Dynamics using Block Coordinate Descent

Paarth Shah, Avadesh Meduri, Wolfgang Merkt +3

In this paper we explore the use of block coordinate descent (BCD) to optimize the centroidal momentum dynamics for dynamically consistent multi-contact behaviors. The centroidal d…

cs.RO2021★ 14 cited

HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems

Carlo Tiseo, Wolfgang Merkt, Keyhan Kouhkiloui Babarahmati +4

Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their propr…

cs.RO2021★ 12 cited

Simultaneous Scene Reconstruction and Whole-Body Motion Planning for Safe Operation in Dynamic Environments

Mark Nicholas Finean, Wolfgang Merkt, Ioannis Havoutis

Recent work has demonstrated real-time mapping and reconstruction from dense perception, while motion planning based on distance fields has been shown to achieve fast, collision-fr…

cs.RO2021

CPG-ACTOR: Reinforcement Learning for Central Pattern Generators

Luigi Campanaro, Siddhant Gangapurwala, Daniele De Martini +2

Central Pattern Generators (CPGs) have several properties desirable for locomotion: they generate smooth trajectories, are robust to perturbations and are simple to implement. Alth…