Search Results for author: Michael Mistry

Found 7 papers, 2 papers with code

What Robot do I Need? Fast Co-Adaptation of Morphology and Control using Graph Neural Networks

no code implementations3 Nov 2021 Kevin Sebastian Luck, Roberto Calandra, Michael Mistry

The co-adaptation of robot morphology and behaviour becomes increasingly important with the advent of fast 3D-manufacturing methods and efficient deep reinforcement learning algorithms.

Exploiting Spherical Projections To Generate Human-Like Wrist Pointing Movements

no code implementations8 Mar 2021 Carlo Tiseo, Sydney Rebecca Charitos, Michael Mistry

The mechanism behind the generation of human movements is of great interest in many fields (e. g. robotics and neuroscience) to improve therapies and technologies.

Robotics

Iterative Semi-parametric Dynamics Model Learning For Autonomous Racing

no code implementations17 Nov 2020 Ignat Georgiev, Christoforos Chatzikomis, Timo Völkl, Joshua Smith, Michael Mistry

In this paper, we develop and apply an iterative learning semi-parametric model, with a neural network, to the task of autonomous racing with a Model Predictive Controller (MPC).

A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots

no code implementations1 Nov 2020 Carlo Tiseo, Vladimir Ivan, Wolfgang Merkt, Ioannis Havoutis, Michael Mistry, Sethu Vijayakumar

In literature, there are multiple model- and learning-based approaches that require significant computational resources to be effectively deployed and they may have limited generality.

Robotics

Robust High-Transparency Haptic Exploration for Dexterous Telemanipulation

no code implementations3 Mar 2020 Keyhan Kouhkiloui Babarahmati, Carlo Tiseo, Quentin Rouxel, Zhibin Li, Michael Mistry

The results show that the proposed control architecture has higher transparency of interaction compared to the impedance controller.

Robotics

Adversarial Generation of Informative Trajectories for Dynamics System Identification

1 code implementation2 Mar 2020 Marija Jegorova, Joshua Smith, Michael Mistry, Timothy Hospedales

Dynamic System Identification approaches usually heavily rely on the evolutionary and gradient-based optimisation techniques to produce optimal excitation trajectories for determining the physical parameters of robot platforms.

Online Simultaneous Semi-Parametric Dynamics Model Learning

1 code implementation9 Oct 2019 Joshua Smith, Michael Mistry

Accurate models of robots' dynamics are critical for control, stability, motion optimization, and interaction.

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