55 citations · 60 across the 28 of their papers we have counts for
16 papers · 1 filter
An End-to-End Framework for Modelling Pneumatic Soft Robots Based on Differentiable Finite Element Methods
Shaohong Zhong, Yao Yao, Perla Maiolino +1
Soft robots present significant modelling challenges due to their non-linearity, complex dynamics and potentially intricate geometries. These difficulties in accurate system identi…
PneuTac: Tactile Manipulation with Soft Pneumatic Robots via Unified MPM-Gaussian Splatting Simulation
Shaohong Zhong, Marco Pontin, Joe Watson +2
Soft robots and tactile sensors have demonstrated great potential in delicate manipulation tasks. Soft pneumatic robots enable safe contact through compliance, and vision-based tac…
Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models
Tianyou Wang, Anson Lei, Joe Watson +1
Imitation learning has emerged as a powerful paradigm for learning visuomotor policies, but its generalisation and stability are limited by the scale and quality of demonstration d…
Sim-to-Real Transfer for Muscle-Actuated Robots via Generalized Actuator Networks
Jan Schneider, Mridul Mahajan, Le Chen +4
Tendon drives paired with soft muscle actuation enable faster and safer robots while potentially accelerating skill acquisition. Still, these systems are rarely used in practice du…
Vision-Language-Action Models for Robotics: A Review Towards Real-World Applications
Kento Kawaharazuka, Jihoon Oh, Jun Yamada +2
Amid growing efforts to leverage advances in large language models (LLMs) and vision-language models (VLMs) for robotics, Vision-Language-Action (VLA) models have recently gained s…
Building Gradient by Gradient: Decentralised Energy Functions for Bimanual Robot Assembly
Alexander L. Mitchell, Joe Watson, Ingmar Posner
There are many challenges in bimanual assembly, including high-level sequencing, multi-robot coordination, and low-level, contact-rich operations such as component mating. Task and…
Grasp-MPC: Closed-Loop Visual Grasping via Value-Guided Model Predictive Control
Jun Yamada, Adithyavairavan Murali, Ajay Mandlekar +3
Grasping of diverse objects in unstructured environments remains a significant challenge. Open-loop grasping methods, effective in controlled settings, struggle in cluttered enviro…
Is Single-View Mesh Reconstruction Ready for Robotics?
Frederik Nolte, Andreas Geiger, Bernhard Schölkopf +1
This paper evaluates single-view mesh reconstruction models for their potential in enabling instant digital twin creation for real-time planning and dynamics prediction using physi…
Task and Joint Space Dual-Arm Compliant Control
Alexander L. Mitchell, Tobit Flatscher, Ingmar Posner
Robots that interact with humans or perform delicate manipulation tasks must exhibit compliance. However, most commercial manipulators are rigid and suffer from significant frictio…
COMBO-Grasp: Learning Constraint-Based Manipulation for Bimanual Occluded Grasping
Jun Yamada, Alexander L. Mitchell, Jack Collins +1
This paper addresses the challenge of occluded robot grasping, i.e. grasping in situations where the desired grasp poses are kinematically infeasible due to environmental constrain…
Offline Adaptation of Quadruped Locomotion using Diffusion Models
Reece O'Mahoney, Alexander L. Mitchell, Wanming Yu +2
We present a diffusion-based approach to quadrupedal locomotion that simultaneously addresses the limitations of learning and interpolating between multiple skills and of (modes) o…
A Review of Differentiable Simulators
Rhys Newbury, Jack Collins, Kerry He +4
Differentiable simulators continue to push the state of the art across a range of domains including computational physics, robotics, and machine learning. Their main value is the a…
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…
D-Cubed: Latent Diffusion Trajectory Optimisation for Dexterous Deformable Manipulation
Jun Yamada, Shaohong Zhong, Jack Collins +1
Mastering dexterous robotic manipulation of deformable objects is vital for overcoming the limitations of parallel grippers in real-world applications. Current trajectory optimisat…
DreamUp3D: Object-Centric Generative Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer
Yizhe Wu, Haitz Sáez de Ocáriz Borde, Jack Collins +2
3D scene understanding for robotic applications exhibits a unique set of requirements including real-time inference, object-centric latent representation learning, accurate 6D pose…
TWIST: Teacher-Student World Model Distillation for Efficient Sim-to-Real Transfer
Jun Yamada, Marc Rigter, Jack Collins +1
Model-based RL is a promising approach for real-world robotics due to its improved sample efficiency and generalization capabilities compared to model-free RL. However, effective m…