no code implementations • 10 Jul 2023 • Riccardo Parosi, Mattia Risiglione, Darwin G. Caldwell, Claudio Semini, Victor Barasuol
We demonstrate the performance and robustness of the proposed approach with various experiments on our 140 kg HyQReal quadruped robot equipped with a 7-DoF manipulator arm.
no code implementations • 1 Apr 2021 • Sunny Katyara, Fanny Ficuciello, Tao Teng, Fei Chen, Bruno Siciliano, Darwin G. Caldwell
Designing robotic tasks for co-manipulation necessitates to exploit not only proprioceptive but also exteroceptive information for improved safety and autonomy.
no code implementations • 26 Aug 2020 • Sunny Katyara, Fanny Ficuciello, Darwin G. Caldwell, Fei Chen, Bruno Siciliano
The Natural Admittance Controller (NAC) is applied to deal with the dynamics of vines.
Robotics Systems and Control Systems and Control
no code implementations • 15 Sep 2019 • Yanlong Huang, Darwin G. Caldwell
Several examples including simulated writing and locomotion tasks are presented to show the effectiveness of our framework.
1 code implementation • 23 May 2019 • Domingo Esteban, Leonel Rozo, Darwin G. Caldwell
Moreover, such composition of individual policies is usually performed sequentially, which is not suitable for tasks that require to perform the subtasks concurrently.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 9 Apr 2019 • Bernardo Aceituno-Cabezas, Carlos Mastalli, Hongkai Dai, Michele Focchi, Andreea Radulescu, Darwin G. Caldwell, Jose Cappelletto, Juan C. Grieco, Gerardo Fernandez-Lopez, Claudio Semini
In this paper, we propose a mixed-integer convex formulation to plan simultaneously contact locations, gait transitions and motion, in a computationally efficient fashion.
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 • 23 Mar 2019 • Anh Nguyen, Thanh-Toan Do, Ian Reid, Darwin G. Caldwell, Nikos G. Tsagarakis
We propose V2CNet, a new deep learning framework to automatically translate the demonstration videos to commands that can be directly used in robotic applications.
no code implementations • 5 Mar 2019 • João Silvério, Yanlong Huang, Fares J. Abu-Dakka, Leonel Rozo, Darwin G. Caldwell
This rich set of information is used in combination with optimal controller fusion to learn actions from data, with two main advantages: i) robots become safe when uncertain about their actions and ii) they are able to leverage partial demonstrations, given as elementary sub-tasks, to optimally perform a higher level, more complex task.
1 code implementation • 16 Mar 2018 • Anh Nguyen, Thanh-Toan Do, Ian Reid, Darwin G. Caldwell, Nikos G. Tsagarakis
The key idea of our approach is the use of object descriptions to provide the detailed understanding of an object.
no code implementations • 19 Dec 2017 • João Silvério, Yanlong Huang, Leonel Rozo, Sylvain Calinon, Darwin G. Caldwell
When learning skills from demonstrations, one is often required to think in advance about the appropriate task representation (usually in either operational or configuration space).
no code implementations • 1 Oct 2017 • Anh Nguyen, Dimitrios Kanoulas, Luca Muratore, Darwin G. Caldwell, Nikos G. Tsagarakis
We present a new method to translate videos to commands for robotic manipulation using Deep Recurrent Neural Networks (RNN).
1 code implementation • 22 Aug 2017 • Anh Nguyen, Thanh-Toan Do, Darwin G. Caldwell, Nikos G. Tsagarakis
Our method first creates the event image from a list of events that occurs in a very short time interval, then a Stacked Spatial LSTM Network (SP-LSTM) is used to learn the camera pose.