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Ashwini Shukla
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 11
Citations - 341
Ashwini Shukla is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: iCub & Attractor. The author has an hindex of 6, co-authored 11 publications receiving 280 citations. Previous affiliations of Ashwini Shukla include Indian Institute of Technology Kanpur.
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Journal ArticleDOI
Catching Objects in Flight
TL;DR: This work proposes a new methodology to find a feasible catching configuration in a probabilistic manner and uses the dynamical systems approach to encode motion from several demonstrations, which enables a rapid and reactive adaptation of the arm motion in the presence of sensor uncertainty.
Journal ArticleDOI
Coupled dynamical system based arm-hand grasping model for learning fast adaptation strategies
Ashwini Shukla,Aude Billard +1 more
TL;DR: A coupled dynamical system based controller is developed, whereby two dynamical systems driving the hand and finger motions are coupled, which offers a compact encoding for reach-to-grasp motions that ensures fast adaptation with zero latency for re-planning.
Journal ArticleDOI
A direct variational method for planning monotonically optimal paths for redundant manipulators in constrained workspaces
TL;DR: This paper proposes a path planner for serial manipulators with a large number of degrees of freedom, working in cluttered workspaces that uses a global approach to search for feasible paths and at the same time involves no pre-processing task.
Journal ArticleDOI
Role of Gaze Cues in Interpersonal Motor Coordination: Towards Higher Affiliation in Human-Robot Interaction.
TL;DR: This work confirms that people can exploit gaze cues to predict another person’s movements and to better coordinate their motions with their partners, even when the partner is a computer-animated avatar.
Proceedings ArticleDOI
Reaching and grasping kitchenware objects
Rui Figueiredo,Ashwini Shukla,Duarte Aragao,Plinio Moreno,Alexandre Bernardino,José Santos-Victor,Aude Billard +6 more
TL;DR: This work integrates software components that allow efficient and successful grasping of kitchenware objects that include the object pose detector, the gripper reaching motion and the grasp hypothesis selection.