142 citations · 519 across the 33 of their papers we have counts for
36 papers
You Only Look at One: Category-Level Object Representations for Pose Estimation From a Single Example
Walter Goodwin, Ioannis Havoutis, Ingmar Posner
In order to meaningfully interact with the world, robot manipulators must be able to interpret objects they encounter. A critical aspect of this interpretation is pose estimation:…
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…
Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Space
Jun Yamada, Chia-Man Hung, Jack Collins +2
Motion planning framed as optimisation in structured latent spaces has recently emerged as competitive with traditional methods in terms of planning success while significantly out…
Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation
Chia-Man Hung, Shaohong Zhong, Walter Goodwin +4
We present a novel approach to path planning for robotic manipulators, in which paths are produced via iterative optimisation in the latent space of a generative model of robot pos…
Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion
Siddhant Gangapurwala, Luigi Campanaro, Ioannis Havoutis
Robotic locomotion is often approached with the goal of maximizing robustness and reactivity by increasing motion control frequency. We challenge this intuitive notion by demonstra…
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…
Zero-Shot Category-Level Object Pose Estimation
Walter Goodwin, Sagar Vaze, Ioannis Havoutis +1
Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally. In this paper we tackle the problem of estima…
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…
BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning
Avadesh Meduri, Paarth Shah, Julian Viereck +3
Online planning of whole-body motions for legged robots is challenging due to the inherent nonlinearity in the robot dynamics. In this work, we propose a nonlinear MPC framework, t…
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…
Semantically Grounded Object Matching for Robust Robotic Scene Rearrangement
Walter Goodwin, Sagar Vaze, Ioannis Havoutis +1
Object rearrangement has recently emerged as a key competency in robot manipulation, with practical solutions generally involving object detection, recognition, grasping and high-l…
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…
Receding-Horizon Perceptive Trajectory Optimization for Dynamic Legged Locomotion with Learned Initialization
Oliwier Melon, Romeo Orsolino, David Surovik +3
To dynamically traverse challenging terrain, legged robots need to continually perceive and reason about upcoming features, adjust the locations and timings of future footfalls and…
Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery
Chia-Man Hung, Li Sun, Yizhe Wu +2
End-to-end visuomotor control is emerging as a compelling solution for robot manipulation tasks. However, imitation learning-based visuomotor control approaches tend to suffer from…
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…
RLOC: Terrain-Aware Legged Locomotion using Reinforcement Learning and Optimal Control
Siddhant Gangapurwala, Mathieu Geisert, Romeo Orsolino +2
We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize on-board proprioceptive…
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…