15 accepted papers
Humans possess a remarkable ability to react to unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to maintain balance. Inspired by this behavior, we propose a novel design of a robotic leg utilizing fibre jamming. The research h
Mobile robot teams often require decentralised autonomous navigation through narrow gaps in limited commu- nication environments (e.g., underground search-and-rescue op- erations). Existing navigation approaches exhibit suboptimal per- formance for avoiding multi-robot collisions in such bottlenecks…
Reinforcement Learning (RL) robot controllers usually aggregate many task objectives into one scalar reward. While large-scale proximal policy optimisation (PPO) has enabled impressive results such as robust real-world robot locomotion, many tasks still require careful reward tuning and remain britt…
Soft robotics has emerged as the standard solution for grasping deformable objects, and has proven invaluable for mobile robotic exploration in extreme environments. However, despite this growth, there are no widely adopted computational design tools that produce quality, manufacturable designs. To…
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 simulations and then calibrated against real observations. Current machine learning approaches, however, mostly rely on rerunn…
Modelling complex deformation for soft robotics provides a guideline to understand their behaviour, leading to safe interaction with the environment. However, building a surrogate model with high accuracy and fast inference speed can be challenging for soft robotics due to the nonlinearity from comp…
Fibre jamming is a new and understudied soft robotic mechanism that has previously found success in stiffness-tunable arms and fingers. However, to date researchers have not fully taken advantage of the freedom offered by contemporary fabrication techniques including multi-material 3D printing in th…
A long short-term memory neural network is used to provide a system model that captures the temporal-dynamics of a holonomic, fully-actuated aquatic surface vehicle. As is true in many fields, new developments in robotics often are made in simulation first before being applied to real systems. To si…
Legged robots are popular candidates for missions in challenging terrains due to their versatile locomotion strategies. Terrain classification is a key enabling technology for autonomous legged robots, allowing them to harness their innate flexibility to adapt to the demands of their operating envir
Telerobotic systems combined with miniaturised snake-like or elephant-trunk robotic arms can improve the ergonomics and accessibility in minimally invasive surgical tasks such as knee arthroscopy. Such systems, however, are usually designed in a specific and integral approach, making it expensive to…
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 dataset. Users are given various simulated manipulation tasks with assigned protocols having the objective of replicating th
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 hardware without the need for physical access. The `reality gap' prevents solutions developed or learnt in simulation from…
Evolutionary algorithms have previously shown promise in generating controllers for legged robots. Multiple evaluations across many evolutionary generations are typically required - simulators are frequently used to accommodate this. However, performance degradation is frequently observed when trans…
We describe an experimental platform that uses an evolutionary algorithm to automatically tune the gains of a cascaded PID quadcopter controller. All parameters are tuned simultaneously, few platform assumptions are necessary, and no modeling is required. The platform is able to run back-to-back exp…