no code implementations • 18 Sep 2022 • João Silvério, Yanlong Huang
Over the last two decades, the robotics community witnessed the emergence of various motion representations that have been used extensively, particularly in behavorial cloning, to compactly encode and generalize skills.
no code implementations • 15 Sep 2022 • Antonin Raffin, Daniel Seidel, Jens Kober, Alin Albu-Schäffer, João Silvério, Freek Stulp
Spring-based actuators in legged locomotion provide energy-efficiency and improved performance, but increase the difficulty of controller design.
1 code implementation • 12 Jan 2021 • Suhan Shetty, João Silvério, Sylvain Calinon
In robotics, ergodic control extends the tracking principle by specifying a probability distribution over an area to cover instead of a trajectory to track.
Robotics Systems and Control Systems and Control Dynamical Systems Optimization and Control Applications
no code implementations • 7 Oct 2020 • Emmanuel Pignat, João Silvério, Sylvain Calinon
In particular, we show that the proposed approach can be extended to PoE with a nullspace structure (PoENS), where the model is able to recover tasks that are masked by the resolution of higher-level objectives.
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.
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).