no code implementations • 7 Apr 2019 • Carlos Mastalli, Ioannis Havoutis, Alexander W. Winkler, Darwin G. Caldwell, Claudio Semini
We use a lattice representation together with a set of defined body movement primitives for computing a body action plan.
no code implementations • 22 Feb 2020 • Siddhant Gangapurwala, Alexander Mitchell, Ioannis Havoutis
Deep reinforcement learning (RL) uses model-free techniques to optimize task-specific control policies.
no code implementations • 3 Jul 2020 • Alexander L. Mitchell, Martin Engelcke, Oiwi Parker Jones, David Surovik, Siddhant Gangapurwala, Oliwier Melon, Ioannis Havoutis, Ingmar Posner
In addition, kinodynamic constraints are often non-differentiable and difficult to implement in an optimisation approach.
no code implementations • 3 Aug 2020 • Mark Nicholas Finean, Wolfgang Merkt, Ioannis Havoutis
We present a novel framework for motion planning in dynamic environments that accounts for the predicted trajectories of moving objects in the scene.
Motion Planning Robotics Systems and Control Systems and Control
no code implementations • 2 Oct 2020 • Wolfgang Merkt, Vladimir Ivan, Traiko Dinev, Ioannis Havoutis, Sethu Vijayakumar
We demonstrate our method on a cart-pole toy problem and a quadrotor avoiding obstacles, and show that clustering samples based on inherent structure improves the warm-start quality.
no code implementations • 1 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
1 code implementation • 5 Dec 2020 • Siddhant Gangapurwala, Mathieu Geisert, Romeo Orsolino, Maurice Fallon, Ioannis Havoutis
We evaluate the robustness of our method over a wide variety of complex terrains.
no code implementations • 25 Feb 2021 • Luigi Campanaro, Siddhant Gangapurwala, Daniele De Martini, Wolfgang Merkt, Ioannis Havoutis
Our results on a locomotion task using a single-leg hopper demonstrate that explicitly using the CPG as the Actor rather than as part of the environment results in a significant increase in the reward gained over time (6x more) compared with previous approaches.
Robotics
no code implementations • 22 Mar 2021 • Chia-Man Hung, Li Sun, Yizhe Wu, Ioannis Havoutis, Ingmar Posner
To recover from high uncertainty cases, the robot monitors its uncertainty along a trajectory and explores possible actions in the state-action space to bring itself to a more certain state.
1 code implementation • 15 Nov 2021 • Walter Goodwin, Sagar Vaze, Ioannis Havoutis, Ingmar Posner
Object rearrangement has recently emerged as a key competency in robot manipulation, with practical solutions generally involving object detection, recognition, grasping and high-level planning.
no code implementations • 9 Dec 2021 • Alexander L. Mitchell, Wolfgang Merkt, Mathieu Geisert, Siddhant Gangapurwala, Martin Engelcke, Oiwi Parker Jones, Ioannis Havoutis, Ingmar Posner
This encourages disentanglement such that application of a drive signal to a single dimension of the latent state induces holistic plans synthesising a continuous variety of trot styles.
no code implementations • 14 Mar 2022 • Carlos Mastalli, Wolfgang Merkt, Guiyang Xin, Jaehyun Shim, Michael Mistry, Ioannis Havoutis, Sethu Vijayakumar
To the best of our knowledge, our predictive controller is the first to handle actuation limits, generate agile locomotion maneuvers, and execute optimal feedback policies for low level torque control without the use of a separate whole-body controller.
1 code implementation • 7 Apr 2022 • Walter Goodwin, Sagar Vaze, Ioannis Havoutis, Ingmar Posner
Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally.
no code implementations • 2 May 2022 • Alexander L. Mitchell, Wolfgang Merkt, Mathieu Geisert, Siddhant Gangapurwala, Martin Engelcke, Oiwi Parker Jones, Ioannis Havoutis, Ingmar Posner
We evaluate our approach on two versions of the real ANYmal quadruped robots and demonstrate that our method achieves a continuous blend of dynamic trot styles whilst being robust and reactive to external perturbations.
no code implementations • 26 Sep 2022 • Luigi Campanaro, Siddhant Gangapurwala, Wolfgang Merkt, Ioannis Havoutis
This allows us to obtain locomotion policies that are robust to variations in system dynamics.
3 code implementations • 29 Sep 2022 • Siddhant Gangapurwala, Luigi Campanaro, Ioannis Havoutis
Robotic locomotion is often approached with the goal of maximizing robustness and reactivity by increasing motion control frequency.
no code implementations • 21 Oct 2022 • Chia-Man Hung, Shaohong Zhong, Walter Goodwin, Oiwi Parker Jones, Martin Engelcke, Ioannis Havoutis, Ingmar Posner
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 poses.
no code implementations • 6 Mar 2023 • Jun Yamada, Chia-Man Hung, Jack Collins, Ioannis Havoutis, Ingmar Posner
Motion planning framed as optimisation in structured latent spaces has recently emerged as competitive with traditional methods in terms of planning success while significantly outperforming them in terms of computational speed.
no code implementations • 25 Apr 2023 • Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala, Wolfgang Merkt, Ioannis Havoutis
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 noise during deployment without explicitly modelling its distribution for each state.
no code implementations • 22 May 2023 • Walter Goodwin, Ioannis Havoutis, Ingmar Posner
In this work, we present a method for achieving category-level pose estimation by inspection of just a single object from a desired category.