Publications (61)
Hybrid Soft Electrostatic Metamaterial Gripper for Multi-surface, Multi-object Adaptation
Ryo Kanno, Pham H. Nguyen, Joshua Pinskier +3
One of the trendsetting themes in soft robotics has been the goal of developing the ultimate universal soft robotic gripper. One that is capable of manipulating items of various sh…
Towards the Targeted Environment-Specific Evolution of Robot Components
Jack Collins, Wade Geles, David Howard +1
This research considers the task of evolving the physical structure of a robot to enhance its performance in various environments, which is a significant problem in the field of Ev…
Programmable Telescopic Soft Pneumatic Actuators for Deployable and Shape Morphing Soft Robots
Joel Kemp, Andre Farinha, David Howard +2
Soft Robotics presents a rich canvas for free-form and continuum devices capable of exerting forces in any direction and transforming between arbitrary configurations. However, the…
Soft Pneumatic Grippers: Topology optimization, 3D-printing and Experimental validation
Prabhat Kumar, Chandra Prakash, Josh Pinskier +2
Typically, heuristic/trial-based approaches are used to design soft pneumatic grippers (SPGs). This paper presents a systematic topology optimization framework for developing SPGs.…
Shape, Size, and Fabrication Effects in 3D Printed Granular Jamming Grippers
David Howard, Jack O'Connor, James Brett +1
Granular jamming is a popular soft actuation mechanism that provides high stiffness variability with minimum volume variation. Jamming is particularly interesting from a design per…
Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors
Llewyn Salt, David Howard, Giacomo Indiveri +1
The Lobula Giant Movement Detector (LGMD) is an identified neuron of the locust that detects looming objects and triggers the insect's escape responses. Understanding the neural pr…
Evolving Spiking Neural Networks for Nonlinear Control Problems
Huanneng Qiu, Matthew Garratt, David Howard +1
Spiking Neural Networks are powerful computational modelling tools that have attracted much interest because of the bioinspired modelling of synaptic interactions between neurons.…
A rainbow -partite version of the ErdÅs-Ko-Rado theorem
Ron Aharoni, David Howard
Let be the minimal number such that every hypergraph larger than contained in contains a matching of size , and let be the mini…
Revolutionaries and Spies
David Howard, Clifford Smyth
Let be a graph and let be positive integers. "Revolutionaries and Spies", denoted $\cG(G,r,s,k)$, is the following two-player game. The sets of positions for pl…
Cross-intersecting pairs of hypergraphs
Ron Aharoni, David Howard
Two hypergraphs are called {\em cross-intersecting} if for every pair of edges . Each of the hypergraphs is then…
A Compliant Robotic Leg Based on Fibre Jamming
Lois Liow, James Brett, Josh Pinskier +4
Humans possess a remarkable ability to react to unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to maintai…
Topology optimization of fluidic pressure-driven multi-material compliant mechanisms
Prabhat Kumar, Josh Pinskier, David Howard +1
Compliant mechanisms actuated by pneumatic loads are receiving increasing attention due to their direct applicability as soft robots that perform tasks using their flexible bodies.…
Real World Morphological Evolution is Feasible
Tonnes F. Nygaard, David Howard, Kyrre Glette
Evolutionary algorithms offer great promise for the automatic design of robot bodies, tailoring them to specific environments or tasks. Most research is done on simplified models o…
Grasp Synthesis Matching From Rigid To Soft Robot Grippers Using Conditional Flow Matching
Tanisha Parulekar, Ge Shi, Josh Pinskier +2
A representation gap exists between grasp synthesis for rigid and soft grippers. Anygrasp [1] and many other grasp synthesis methods are designed for rigid parallel grippers, and a…
Active Vibration Fluidization for Granular Jamming Grippers
Cameron Coombe, James Brett, Raghav Mishra +2
Granular jamming has recently become popular in soft robotics with widespread applications including industrial gripping, surgical robotics and haptics. Previous work has investiga…
A Comprehensive Dataset of Grains for Granular Jamming in Soft Robotics: Grip Strength and Shock Absorption
David Howard, Jack O'Connor, Jordan Letchford +4
We test grip strength and shock absorption properties of various granular material in granular jamming robotic components. The granular material comprises a range of natural, manuf…
RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment
Humphrey Munn, Brendan Tidd, Peter Bohm +2
Deploying learned control policies is risky because policies that appear robust in simulation can confidently enter out-of-distribution (OOD) states after Sim-to-Real transfer, cau…
On a Generalization of the Ryser-Brualdi-Stein Conjecture
Ron Aharoni, Pierre Charbit, David Howard
A rainbow matching for (not necessarily distinct) sets F_1,...,F_k of hypergraph edges is a matching consisting of k edges, one from each F_i. The aim of the paper is twofold - to…
Whole-Body Dynamic Throwing with Legged Manipulators
Humphrey Munn, Brendan Tidd, Peter Böhm +2
Throwing with a legged robot involves precise coordination of object manipulation and locomotion - crucial for advanced real-world interactions. Most research focuses on either man…
A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers
David Howard, Larry Bull, Pier-Luca Lanzi
Learning Classifier Systems (LCS) are population-based reinforcement learners that were originally designed to model various cognitive phenomena. This paper presents an explicitly…
Follow the Gradient: Crossing the Reality Gap using Differentiable Physics (RealityGrad)
Jack Collins, Ross Brown, Jürgen Leitner +1
We propose a novel iterative approach for crossing the reality gap that utilises live robot rollouts and differentiable physics. Our method, RealityGrad, demonstrates for the first…
HRI-SA: A Multimodal Dataset for Online Assessment of Human Situational Awareness during Remote Human-Robot Teaming
Hashini Senaratne, Richard Attfield, Samith Widhanapathirana +4
Maintaining situational awareness (SA) is critical in human-robot teams. Yet, under high workload and dynamic conditions, operators often experience SA gaps. Automated detection of…
A 'MAP' to find high-performing soft robot designs: Traversing complex design spaces using MAP-elites and Topology Optimization
Yue Xie, Josh Pinskier, Lois Liow +2
Soft robotics has emerged as the standard solution for grasping deformable objects, and has proven invaluable for mobile robotic exploration in extreme environments. However, despi…
The Width of Downsets
Dwight Duffus, David Howard, Imre Leader
How large an antichain can we find inside a given downset in the lattice of subsets of [n]? Sperner's theorem asserts that the largest antichain in the whole lattice has size the b…
Alternative Interfaces for Human-initiated Natural Language Communication and Robot-initiated Haptic Feedback: Towards Better Situational Awareness in Human-Robot Collaboration
Callum Bennie, Bridget Casey, Cecile Paris +9
This article presents an implementation of a natural-language speech interface and a haptic feedback interface that enables a human supervisor to provide guidance to, request infor…
Prospectively accelerated dynamic speech MRI at 3 Tesla using a self-navigated spiral based manifold regularized scheme
Rushdi Zahid Rusho, Abdul Haseeb Ahmed, Stanley Kruger +6
This work proposes a self-navigated variable density spiral(VDS) based manifold regularization scheme to prospectively improve dynamic speech MRI at 3T. Short readout 1.3ms spirals…
Benchmarking Simulated Robotic Manipulation through a Real World Dataset
Jack Collins, Jessie McVicar, David Wedlock +3
We present a benchmark to facilitate simulated manipulation; an attempt to overcome the obstacles of physical benchmarks through the distribution of a real world, ground truth data…
SimTO: A two-stage, simulation-driven topology optimization framework for bespoke soft robotic grippers
Kurt Enkera, Josh Pinskier, Marcus Gallagher +1
Soft robotic grippers are essential for grasping delicate, geometrically complex objects in manufacturing, healthcare and agriculture. However, existing designs struggle to grasp f…
ReefFlex: A Generative Design Framework for Soft Robotic Grasping of Organic and Fragile objects
Josh Pinskier, Sarah Baldwin, Stephen Rodan +1
Climate change, invasive species and human activities are currently damaging the world's coral reefs at unprecedented rates, threatening their vast biodiversity and fisheries, and…
Quantifying the Reality Gap in Robotic Manipulation Tasks
Jack Collins, David Howard, Jürgen Leitner
We quantify the accuracy of various simulators compared to a real world robotic reaching and interaction task. Simulators are used in robotics to design solutions for real world ha…
Vibration Improves Performance in Granular Jamming Grippers
Raghav Mishra, Tyson Philips, Gary W. Delaney +1
Granular jamming is a popular soft robotics technology that has seen recent widespread applications including industrial gripping, surgical robotics and haptics. However, to date t…
Environmental Adaptation of Robot Morphology and Control through Real-world Evolution
Tønnes F. Nygaard, Charles P. Martin, David Howard +2
Robots operating in the real world will experience a range of different environments and tasks. It is essential for the robot to have the ability to adapt to its surroundings to wo…
Diversity-based Design Assist for Large Legged Robots
David Howard, Thomas Lowe, Wade Geles
We combine MAP-Elites and highly parallelisable simulation to explore the design space of a class of large legged robots, which stand at around 2m tall and whose design and constru…
Generalized Task-Driven Design of Soft Robots via Reduced-Order FEM-based Surrogate Modeling
Yao Yao, David Howard, Perla Maiolino
Task-driven design of soft robots requires models that are physically accurate and computationally efficient, while remaining transferable across actuator designs and task scenario…
Large rainbow matchings in general graphs
Ron Aharoni, Eli Berger, Maria Chudnovsky +2
By a theorem of Drisko, any matchings of size in a bipartite graph have a partial rainbow matching of size . Inspired by discussion of Barát, Gyárfás and Sárközy…
An Experimental Characterization of Mechanical Layer Jamming Systems
Jessica Gumowski, Krishna Manaswi Digumarti, David Howard
Organisms in nature, such as Cephalopods and Pachyderms, exploit stiffness modulation to achieve amazing dexterity in the control of their appendages. In this paper, we explore the…
Towards Crossing the Reality Gap with Evolved Plastic Neurocontrollers
Huanneng Qiu, Matthew Garratt, David Howard +1
A critical issue in evolutionary robotics is the transfer of controllers learned in simulation to reality. This is especially the case for small Unmanned Aerial Vehicles (UAVs), as…
Evolving embodied intelligence from materials to machines
David Howard, Agoston E. Eiben, Danielle Frances Kennedy +3
Natural lifeforms specialise to their environmental niches across many levels; from low-level features such as DNA and proteins, through to higher-level artefacts including eyes, l…
Semi-supervised Gated Recurrent Neural Networks for Robotic Terrain Classification
Ahmadreza Ahmadi, Tønnes Nygaard, Navinda Kottege +2
Legged robots are popular candidates for missions in challenging terrains due to the wide variety of locomotion strategies they can employ. Terrain classification is a key enabling…
DexGrip: Multi-modal Soft Gripper with Dexterous Grasping and In-hand Manipulation Capacity
Xing Wang, Liam Horrigan, Josh Pinskier +6
The ability of robotic grippers to not only grasp but also re-position and re-orient objects in-hand is crucial for achieving versatile, general-purpose manipulation. While recent…
Jammkle: Fibre jamming 3D printed multi-material tendons and their application in a robotic ankle
James Brett, Katrina Lo Surdo, Lauren Hanson +2
Fibre jamming is a relatively new and understudied soft robotic mechanism that has previously found success when used in stiffness-tuneable arms and fingers. However, to date resea…
Scalable Multi-Objective Robot Reinforcement Learning through Gradient Conflict Resolution
Humphrey Munn, Brendan Tidd, Peter Böhm +2
Reinforcement Learning (RL) robot controllers usually aggregate many task objectives into one scalar reward. While large-scale proximal policy optimisation (PPO) has enabled impres…
Bayesian Adaptive Calibration and Optimal Design
Rafael Oliveira, Dino Sejdinovic, David Howard +1
The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simula…
The Jamming Donut: A Free-Space Gripper based on Granular Jamming
Therese Joseph, Sarah Baldwin, Lillian Guan +2
Fruit harvesting has recently experienced a shift towards soft grippers that possess compliance, adaptability, and delicacy. In this context, pneumatic grippers are popular, due to…
Evolving Unipolar Memristor Spiking Neural Networks
David Howard, Larry Bull, Ben De Lacy Costello
Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristo…
3D Printable Soft Liquid Metal Sensors for Delicate Manipulation Tasks
Lois Liow, Jonty Milford, Emre Uygun +4
Robotics and automation are key enablers to increase throughput in ongoing conservation efforts across various threatened ecosystems. Cataloguing, digitisation, husbandry, and simi…
An Ultrasensitive 3D Printed Tactile Sensor for Soft Robotics
Saeb Mousavi, David Howard, Shuying Wu +1
A new method is presented to manufacture piezoresistive tactile sensors using fused deposition modelling (FDM)printing technology with two different filaments made of thermoplastic…
Getting a Grip: in Materio Evolution of Membrane Morphology for Soft Robotic Jamming Grippers
David Howard, Jack O'Connor, Jordan Letchford +5
The application of granular jamming in soft robotics is a recent and promising new technology offer exciting possibilities for creating higher performance robotic devices. Granular…
Traversing the Reality Gap via Simulator Tuning
Jack Collins, Ross Brown, Jurgen Leitner +1
The large demand for simulated data has made the reality gap a problem on the forefront of robotics. We propose a method to traverse the gap by tuning available simulation paramete…
Path Towards Multilevel Evolution of Robots
Shelvin Chand, David Howard
Multi-level evolution is a bottom-up robotic design paradigm which decomposes the design problem into layered sub-tasks that involve concurrent search for appropriate materials, co…
Comparing Direct and Indirect Representations for Environment-Specific Robot Component Design
Jack Collins, Ben Cottier, David Howard
We compare two representations used to define the morphology of legs for a hexapod robot, which are subsequently 3D printed. A leg morphology occupies a set of voxels in a voxel gr…
Fin-QD: A Computational Design Framework for Soft Grippers: Integrating MAP-Elites and High-fidelity FEM
Yue Xie, Xing Wang, Fumiya Iida +1
Computational design can excite the full potential of soft robotics that has the drawbacks of being highly nonlinear from material, structure, and contact. Up to date, enthusiastic…
EvoRobogami: Co-designing with Humans in Evolutionary Robotics Experiments
Huang Zonghao, Quinn Wu, David Howard +1
We study the effects of injecting human-generated designs into the initial population of an evolutionary robotics experiment, where subsequent population of robots are optimised vi…
Assessing Evolutionary Terrain Generation Methods for Curriculum Reinforcement Learning
David Howard, Josh Kannemeyer, Davide Dolcetti +2
Curriculum learning allows complex tasks to be mastered via incremental progression over `stepping stone' goals towards a final desired behaviour. Typical implementations learn loc…
Differential Evolution and Bayesian Optimisation for Hyper-Parameter Selection in Mixed-Signal Neuromorphic Circuits Applied to UAV Obstacle Avoidance
Llewyn Salt, David Howard, Giacomo Indiveri +1
The Lobula Giant Movement Detector (LGMD) is a an identified neuron of the locust that detects looming objects and triggers its escape responses. Understanding the neural principle…
Automated design of pneumatic soft grippers through design-dependent multi-material topology optimization
Josh Pinskier, Prabhat Kumar, Matthijs Langelaar +1
Soft robotic grasping has rapidly spread through the academic robotics community in recent years and pushed into industrial applications. At the same time, multimaterial 3D printin…
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…
Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions: Adaptation of the DARPA Subterranean Challenge
Nicole Robinson, Jason Williams, David Howard +6
Human operators in human-robot teams are commonly perceived to be critical for mission success. To explore the direct and perceived impact of operator input on task success and tea…
A Framework for Dynamic Situational Awareness in Human Robot Teams: An Interview Study
Hashini Senaratne, Leimin Tian, Pavan Sikka +4
In human-robot teams, human situational awareness is the operator's conscious knowledge of the team's states, actions, plans and their environment. Appropriate human situational aw…
PINN-Ray: A Physics-Informed Neural Network to Model Soft Robotic Fin Ray Fingers
Xing Wang, Joel Janek Dabrowski, Josh Pinskier +4
Modelling complex deformation for soft robotics provides a guideline to understand their behaviour, leading to safe interaction with the environment. However, building a surrogate…
SoGraB: A Visual Method for Soft Grasping Benchmarking and Evaluation
Benjamin G. Greenland, Josh Pinskier, Xing Wang +5
Recent years have seen soft robotic grippers gain increasing attention due to their ability to robustly grasp soft and fragile objects. However, a commonly available standardised e…