22 citations · 126 across the 31 of their papers we have counts for
34 papers
Reference Free Platform Adaptive Locomotion for Quadrupedal Robots using a Dynamics Conditioned Policy
David Rytz, Suyoung Choi, Wanming Yu +3
This article presents Platform Adaptive Locomotion (PAL), a unified control method for quadrupedal robots with different morphologies and dynamics. We leverage deep reinforcement l…
Adaptive Manipulation using Behavior Trees
Jacques Cloete, Wolfgang Merkt, Ioannis Havoutis
Many manipulation tasks pose a challenge since they depend on non-visual environmental information that can only be determined after sustained physical interaction has already begu…
Gaitor: Learning a Unified Representation Across Gaits for Real-World Quadruped Locomotion
Alexander L. Mitchell, Wolfgang Merkt, Aristotelis Papatheodorou +2
The current state-of-the-art in quadruped locomotion is able to produce a variety of complex motions. These methods either rely on switching between a discrete set of skills or lea…
Momentum-Aware Trajectory Optimisation using Full-Centroidal Dynamics and Implicit Inverse Kinematics
Aristotelis Papatheodorou, Wolfgang Merkt, Alexander L. Mitchell +1
The current state-of-the-art gradient-based optimisation frameworks are able to produce impressive dynamic manoeuvres such as linear and rotational jumps. However, these methods, w…
R-LGP: A Reachability-guided Logic-geometric Programming Framework for Optimal Task and Motion Planning on Mobile Manipulators
Kim Tien Ly, Valeriy Semenov, Mattia Risiglione +2
This paper presents an optimization-based solution to task and motion planning (TAMP) on mobile manipulators. Logic-geometric programming (LGP) has shown promising capabilities for…
Perceptive Locomotion through Whole-Body MPC and Optimal Region Selection
Thomas Corbères, Carlos Mastalli, Wolfgang Merkt +6
Real-time synthesis of legged locomotion maneuvers in challenging industrial settings is still an open problem, requiring simultaneous determination of footsteps locations several…
Roll-Drop: accounting for observation noise with a single parameter
Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala +2
This paper proposes a simple strategy for sim-to-real in Deep-Reinforcement Learning (DRL) -- called Roll-Drop -- that uses dropout during simulation to account for observation noi…
Multi-Agent Chance-Constrained Stochastic Shortest Path with Application to Risk-Aware Intelligent Intersection
Majid Khonji, Rashid Alyassi, Wolfgang Merkt +5
In transportation networks, where traffic lights have traditionally been used for vehicle coordination, intersections act as natural bottlenecks. A formidable challenge for existin…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Sparsity-Inducing Optimal Control via Differential Dynamic Programming
Traiko Dinev, Wolfgang Merkt, Vladimir Ivan +2
Optimal control is a popular approach to synthesize highly dynamic motion. Commonly, regularization is used on the control inputs in order to minimize energy used and to ensu…
A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots
Carlo Tiseo, Vladimir Ivan, Wolfgang Merkt +3
Path planning and collision avoidance are challenging in complex and highly variable environments due to the limited horizon of events. In literature, there are multiple model- and…
Inverse Dynamics vs. Forward Dynamics in Direct Transcription Formulations for Trajectory Optimization
Henrique Ferrolho, Vladimir Ivan, Wolfgang Merkt +2
Benchmarks of state-of-the-art rigid-body dynamics libraries report better performance solving the inverse dynamics problem than the forward alternative. Those benchmarks encourage…
Memory Clustering using Persistent Homology for Multimodality- and Discontinuity-Sensitive Learning of Optimal Control Warm-starts
Wolfgang Merkt, Vladimir Ivan, Traiko Dinev +2
Shooting methods are an efficient approach to solving nonlinear optimal control problems. As they use local optimization, they exhibit favorable convergence when initialized with a…
A Feasibility-Driven Approach to Control-Limited DDP
Carlos Mastalli, Wolfgang Merkt, Josep Marti-Saumell +4
Differential dynamic programming (DDP) is a direct single shooting method for trajectory optimization. Its efficiency derives from the exploitation of temporal structure (inherent…